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Doubling of Farmers’ Income by 2022
Issues and Strategies for West Bengal
Study Sponsored By
National Bank for Agriculture and Rural Development
Report Prepared By
SANTADAS GHOSH
Associate Professor in Economics
Department of Economics & Politics
Visva-Bharati, Santiniketan
Study Hosted By
A. K. Dasgupta Centre For Planning and Development
Visva-Bharati; Santiniketan
आर्थिक विश्लेषण और अनुसंधान विभाग
प्लॉटक्रसी-24,'जी' ब्लॉक,बांद्रा-कुलााकॉम्पप्लेक्स, बांद्रा (पूिा), मुंबई - 400 051.
टेली: +91 22 2652 3617 • फ़ै क्स: +91 22 2653 0086 • ईमेल:dear@nabard.org Department of Economic Analysis & Research
Contents
Executive Summary ................................................................................................................................. i
1. Study Background ............................................................................................................................... 1
1.1 Basic information on agriculture in West Bengal ......................................................................... 1
1.2 Agro Climatic Zones ..................................................................................................................... 2
1.3 State Agricultural Plan .................................................................................................................. 3
1.4 Rural Non-farm Sector in India and West Bengal ........................................................................ 5
1.5 Doubling of Farmers‟ Income: Issues and challenges .................................................................. 7
2. Study objective.................................................................................................................................... 8
3. Sample design ..................................................................................................................................... 9
3.1 Selection of sample districts ....................................................................................................... 10
3.2 Selection of sample blocks .......................................................................................................... 10
3.3 Selection of sample villages ........................................................................................................ 12
3.4 Selection of sample households .................................................................................................. 12
3.5 Brief description of information collected .................................................................................. 13
4. Study findings ................................................................................................................................... 13
4.1 Household profile across survey districts ................................................................................... 13
4.2 Cropping pattern and livestock across socio-economic classes .................................................. 19
4.3 Household earning and its composition ...................................................................................... 23
4.4 Delivery of government assistance ............................................................................................. 27
4.5 The rural credit market and credit availability ............................................................................ 30
4.6. Impact of irrigation and credit on farm income ......................................................................... 34
4.7 Households‟ awareness, problems and diversification plans ...................................................... 36
5. Discussions on study findings ........................................................................................................... 39
5.1 Problems with the delivery system of farmers‟ assistance schemes ........................................... 40
5.2 Problems with irrigation infrastructure ....................................................................................... 40
5.3 Problems with rural credit ........................................................................................................... 41
5.4 The role of „progressive farmers‟ and demonstration effect ....................................................... 43
5.5 Scenario building at farm level ................................................................................................... 46
5.6 The Issue of Farmers‟ Clubs ....................................................................................................... 51
5.7 Justification for possible policy interventions............................................................................. 52
6. Conclusion and policy suggestions ................................................................................................... 54
6.1 Recommendations for improving institutions for assistance delivery ........................................ 54
6.2 Recommendations for improving various service provisions to farmers .................................... 55
6.3 Recommendations for increasing farm income in major agro-climatic zones ............................ 55
References ............................................................................................................................................. 56
APPENDIX-1: Location of the Sample districts in West Bengal ......................................................... 58
APPENDIX-2: Characteristics of sample villages ................................................................................ 59
APPENDIX-3: Agro-climatic zone wise Frequency distribution of Non-Farm earning activities of the
sample respondents ............................................................................................................................... 63
APPENDIX-4: Brief description of Farmers‟ Clubs operating in sample villages ............................... 66
APPENDIX-5: Survey Instrument for households ............................................................................... 67
i
Executive Summary
This study was undertaken to provide important baseline estimates for average rural
household income and its composition across four major agro-climatic zones and also across
different social class and landholding size classes for the state of West Bengal in 2017. The
study also identifies the major issues that are confronted by the rural farming households in
their endeavour to increase income from farming and allied activities. Based on the survey
findings, the study makes a number of policy recommendations for quick improvement in the
rural earning scenario for the state as well as for the major agro-climatic zones within it. The
findings and recommendations of this study might provide important policy directions for
„Doubling of Farmers‟ Income by 2022‟ – an announced goal of the Government of India.
The study is entirely based on information collected from primary survey of 809 households
from four major agro-climatic zones in West Bengal and extensive focus group discussions
with stakeholders. Each agro-climatic zone is represented by approximately 200 households.
A carefully designed multistage stratified random sampling method had been used that
ensured capturing maximum possible variability in socio-economic conditions among the
sample households. The field survey was conducted between August-November, 2017.
The study found that an overwhelming majority of the farmers in West Bengal are „marginal‟
and „small‟ according to standard official classification of landholding classes in India. In a
randomly selected sample of households at village level, the survey found very few „semi-
medium‟ and only one „medium‟ farmer in the sample. This is probably a legacy of
successful land reforms in the state in previous decades. The study calculated an overall
average landholding size of rural households to be 0.4 hectare only. Small landholding sizes
also forced people to seek earning avenues outside farm and allied sector. Close to 50 percent
of the survey households were reported to be engaged in some form of non-farm activities as
well.
Among the four major agro-climatic zones, the northern Terai-Alluvial zone is found to be
most advanced in terms of farming activities. This is supplemented by a good amount of
income generated by small tea plantations in the zone due to its special soil properties. The
Lateritic (rain fed) zone is expectedly generating lowest average household income compared
to all other zones. The Coastal Saline zone has the highest population pressure and the
average landholding size in this zone is about 40 percent less than the state‟s average. Still,
this zone is making up for the lack of land resources partially by earning from coastal fishing
and inland fisheries. The average household income of Gangetic Alluvial zone is placed in
between. The estimate for this zone is a bit underestimate than a usual year because of
significant losses in potato cultivation reported by the respondents from this zone in 2017 due
to depressed prices. Potato is the major winter crop in this zone.
The average annual household income was found to be around Rs.58,000 for Terai Alluvial
Zone and the same is estimated at around Rs. 29,000 in the Lateritic zone, with estimates for
other two zones lying in between. However, there is large variation in household earning
within each zone due to variation in households‟ land endowments. The estimates are
recalculated across size classes for the state as a whole. The results show that landless
households are surviving with less than Rs. 2,000 per month, the marginal landholders are
earning around Rs. 3,500 per month and the small and medium farmers are earning around
Rs. 7,500 per month from all sources.
ii
Turning to the income estimates across social classes for the state, it is observed that
Scheduled Tribes are relatively worse off in terms of their absolute value of average annual
earning (around Rs. 23,000 per household), compared to the other social classes. It is
interesting to note that similar estimates for SC, OBC and General caste are fairly comparable
(close to Rs. 38,000 per household) in terms of their value and composition.
The survey also found that the Block Agricultural Offices, the agency in control for
delivering most of the farmers‟ assistance schemes, are often understaffed, resulting in
communication gaps between the possible beneficiaries of these schemes and the delivering
authority. The study found that the capability and sincerity of the Assistant Directors of
Agriculture (ADAs) are very high. But they often fail to address the problems of individual
farmers under his/her Block in absence of sufficient number of ground level official liaison
person with the farmers (Krishi Prayukti Sahayaks, KPS). This deficiency creates hurdles for
the lowly educated farmers as they fail to get access to designated persons who can help them
with consultancy and procedures to avail credit and insurance through government
programmes. This lacunae is benefiting mostly a smaller group of villagers with better
education, landholding and usually with some local political clout. Farmers‟ Clubs (FCs),
which are promoted for more information dissemination, resource sharing and equitable
distribution of benefit schemes, are often controlled by these better-off people. The study
found that local elites tend to corner the benefits from large FCs depriving the ordinary
members who are often naive and ignorant.
This lack of proper delivery system is manifested by some numbers obtained from the
primary survey. It is found that only about 15 percent of land-owning households could avail
any type of crop insurance during last one year. Only about 6 percent of households had done
soil tests for their farm-lands ever. Another 20 percent of households had submitted soil
samples for testing to some middlemen, but they didn‟t get the reports yet.
The survey found that Kishan Credit Card (KCC) is eluding the rural farmers due to lack of
clear land titles and lack of procedural knowledge. Over 80 percent of households in the well-
dispersed sample reported not having KCC. Even households with KCC are facing serious
bottlenecks in availing credit in required quantity and in a timely manner. The respondents
reported non-cooperation from local bank authorities and felt that their apathy to provide loan
under KCC might be due to the bank‟s fear of recovery of such credit.
The study also found that the effect of micro-irrigation on enhancing farm income is
relatively more in Lateritic zone. Effect of credit provision for agriculture can result in the
highest percentage change in return in Terai-alluvial zone. Non-farm business earning can be
promoted most effectively in Coastal saline zone and livestock rearing activities can be
promoted most effectively in the Lateritic zone
The study found that it is not the absence of government sponsored assistance schemes, rather
the absence of appropriate delivery mechanism and institutional bottlenecks that are creating
hurdles for the rural households in their endeavour to enhance income. It is empirically
revealed that the provisions are failing to reach the intended beneficiaries due to information
gaps, which are resulting from inefficient delivery mechanisms and institutional
arrangements.
iii
In light of the major findings stated above, this study makes few policy suggestions to
improve rural income in West Bengal in the short run. Important suggestions are made to
build or reshape the existing delivery institutions dealing with various farmers‟ assistance
programmes. The suggestions are provided in the following three sets:
Suggestions for improving institutions for assistance delivery:
Small and efficient Farmers‟ Groups (FG) are to be promoted similar to women‟s
Self-Help Groups in each Gram Panchayet area. Such FGs should be provided with
funds in larger quantity and with longer repayment period compared to women SHGs.
Such groups should ideally be formed by 10-15 farmers in the neighbourhood
belonging to the same landholding class. The FGs should be formally recognized and
institutionalized.
For effective delivery of the various ongoing assistance and farmers‟ welfare
schemes, experienced Non-Governmental Organizations and/or specialized
professional agencies are to be engaged purely as facilitators for helping the lowly
educated farmers in availing various schemes‟ benefits. Such engagements should be
on the basis of financial incentives to the facilitating agency.
Krishi Vigyan Kendras (KVK) in each district need to be funded to set up their own
extension units in each block of the district and scale up their successful
demonstration projects and create a larger pool of local progressive farmers.
Assistance for income enhancement to rural households in West Bengal should be
specially designed for landless and small landholders. They are the overwhelming
majority in the state. Various current assistance schemes, which are not linked to
landholding size, are being appropriated by the larger landowning households due to
their local clout and proximity with the personnel in the delivering institutions.
Suggestions for improving various service provisions to farmers
For intensification of cropping and hence increasing return from farming, successful
rainwater harvesting models should be scaled up taking cue from IWMP projects from
rain fed areas. The office of the Assistant Director of Agriculture in each block might
be asked to provide the extent of such project possibilities and corresponding funding
requirement for his block in this regard.
Specialized soil testing laboratories needs to be set up adjacent to ADA offices in
each block either purely by engaging private agencies through financial incentives, or
through PPP model. Soil tests reports should be provided in a time-bound way and it
should be accompanied by expert opinion on the optimum cropping pattern and
fertilizer use for that soil.
Prime Ministers‟ Fasal Bima Yojna (PMFBY) should have much wider coverage in
crops across different seasons in West Bengal compared to its present provisions.
West Bengal is characterised by extensive cultivation of vegetables, most of which
are presently not covered under PMFBY
iv
Suggestions for increasing farm income in major agro-climatic zones
The assistance schemes for livestock (free distribution of livestock and fodder) needs
to be more concentrated towards the Lateritic zone as the households in this zone have
a better ongoing practice in livestock maintenance and related activities.
Ongoing IWMP projects in rain fed Lateritic zone should be synchronized with
MGNREGA. The later should be used as a vehicle to create more rainwater
harvesting infrastructure like check-dams and dug-wells in Lateritic zones.
In Terai Alluvial zone, special long term credit schemes should be launched for small
holders who can convert parts of their cropland to small tea plantations. The credit is
needed for them towards land conversion cost and also for the gestation period for
new tea plantations which starts yielding financial returns after three years.
.
In light of much lesser average landholding size in Coastal Saline zone compared to
other zones, potential for enhancing rural household income is more from
development of inland fisheries than providing inputs to farming. Special credit
facilities should be provided in this zone for developing brackish water fish farms.
The amount of credit that can be availed through KCC is insufficient for such
enterprise.
In Gangetic Alluvial zone, more warehousing facilities should be made available for
potato and vegetables by enticing private investors with soft loans. Also, for potato
growers, a longer repayment period of credit is recommended as they often distress
sell their output at lower price for repayment of short term loans.
The results in this study, however, have to be interpreted with a word of caution. Due to the
limit imposed by time and resources, this study had to be carried out with approximately 200
households representing each agro-climatic zone. The large extent of socio-economic and
infrastructural variations within each zone had to be captured within a small sample with a
carefully designed multistage sampling scheme. This could only be achieved through a
purposive (but objective) selection of blocks and villages from each zone. Within a sample
village, households were selected by standard stratified random method. But the blocks and
villages were carefully chosen to capture high, medium and low ranks in terms of their
cropping pattern and irrigation infrastructure. Since the relative prevalence or weight of such
blocks and villages vary cross agro-climatic zones, it will be wrong to directly use the
reported estimates as population estimates. While it is perfectly sensible to use the results for
future comparison and identifying bottlenecks, it might not be wise to extrapolate these
results to find estimates for the whole of West Bengal. For that, a larger sample size for each
zone is advisable, which should be supplemented by required secondary information at block
and Gram Panchayet level. It remains another research agenda and open at this point.
1
1. Study Background
1.1 Basic information on agriculture in West Bengal
West Bengal is a predominantly agrarian state comprising of 2.7 percent of India's
geographical area, but supporting nearly 8 percent of its population. This resulted in high
population density and a low average landholding size (0.77 Ha per household). Among an
estimated 71.23 lakh rural households, 96 percent are small and marginal farmers. However,
the state is bestowed with diverse natural resources and varied agro-climatic conditions which
support cultivation of a wide range of crops. West Bengal ranks first in paddy and vegetable
production in the country. It stands second in potato production. The net cropped area is
52.05 lakh hectare which is 68 percent of the state‟s geographical area and 92 percent of its
arable land. The average cropping intensity is 184 percent1.
An estimated 44 percent of the active work force in the state is engaged in agriculture either
as primarily cultivators or agricultural labourers (NSSO, 2014). However, though leading in
production of many agricultural commodities, the income of the farming households in the
state is one of the lowest in the country due to low average land endowments (Mandal et al,
2017). Table-1 provides some basic socio-economic information of West Bengal at a glance.
Table 1: Basic aggregate information on West Bengal
Geographical Area 88,752 sq. km.
Number of Districts 19
Number of Blocks 341
Population 9.13 million
Rural Population 6.55 million
Urban Population 2.58 million
Population Density 1029 per sq. km
Per capita agriculture land holding Less than 1 ha (about 0.64 ha)
Normal Annual Rainfall 1,234 - 4,136 mm.
Cultivable Area 56.84 lakh ha
Net Sown Area 54.65 lakh ha
Net Cropped Area 52.56 lakh ha.
Cropping intensity 181 %
Area under Forest 11897 sq km
Surface Water Resources 132.90 lakh ha. m
Annual Replenishable Ground Water 30.36 lakh ha. m.
Ultimate Irrigation Potential 70.00 lakh ha.
Total Flood Prone Area 37,660 sq. km.
Coastal Length 280 km. Source: West Bengal State Action Plan on Climate Change
http://www.moef.nic.in/downloads/public-information/West-Bengal-SAPCC.pdf
Increasing population pressure with a low per-capita landholding base has resulted in
diversification of earning activities outside the farm sector. The contribution of agriculture
1 https://wb.gov.in/portal/web/guest/agriculture
2
sector to the state‟s Net State Domestic Product (NSDP) has decreased significantly over
2004-05 to 2014-15 (from 25 percent to 16 percent; Mandal et al, 2017). It is also
indicative of low productivity growth in the state‟s agriculture. Compared to other
agriculturally advanced states in India, West Bengal is yet to experience large scale farm
mechanization. This might be a result of high population pressure and relatively lower labour
cost in the farm sector compared to other advanced states. Mechanization in agriculture
progressed faster in north Indian states. For example, the number of tractors used per
thousand hectares of land in Punjab is 82.5, in Hariyana 62.9 while in West Bengal it is only
2.9. The use of electricity as farm input in West Bengal is 1.25 KW/ha which is only 36
precent of that of Punjab2.
1.2 Agro Climatic Zones India is divided into 15 broad agro climatic regions and West Bengal comes under three of
them. Agriculturally, the three broad regions are Eastern Himalayan Region (Zone II), Lower
Gangetic Plain Region (Zone III) and Eastern Plateau & Hilly Region (Zone VIII). The map
depicting the agro climatic regions is presented below:
Figure 1: Major Agro-Climatic regions in West Bengal
Source: State Agriculture Plan http://rkvy.nic.in/static/SAP/WB/WB.PDF
2http://rkvy.nic.in/static/SAP/WB/WB.PDF
3
These three broad regions are further stratified into six agro-climatic sub regions. Salient
features of these sub regions are as follows:
Zone II: Eastern Himalayan Region
(a) Hills sub region: Covering Darjeeling district: Mainly brown forest soil, acidic in nature.
Annual rainfall varies from 2500-3500mm, high humidity, less sunshine hours, poor soil
depth and quality limits crop productivity. Pre-monsoon showers commences from March.
b.) Terai sub region: Covering Jalpaiguri and Coochbehar district. Soils are mostly sandy to
sandy loams, porous, low in base content, poor in available nutrients; acidic; rainfall varies
from 2000-3200mm; high water table, low water holding capacity, high humidity, less
sunshine hours during the monsoon months and marginality of lands in some parts limit crop
productivity.
Zone III: Lower Gangetic Region
(a) Old alluvium: Comprising North and South Dinajpur and Malda districts. Soils are mildly
acidic to neutral; fairly fertile over most of the sub region; rainfall 1500-2000mm in upper
and 1300-1500m in lower parts, considerable area is flood prone.
(b) New alluvium: Covering Murshidabad, Nadia, Hoogly, Burdwan and North 24 Parganas.
Soils are deep, mostly neutral and fertile; rainfall 1350-1450 mm; agriculturally most
productive area of the state.
(c) Coastal saline: Covering South 24 Parganas, Howrah and Midnapore (East). Soils are
mostly heavy clay containing higher salts of sodium, magnesium, potassium with organic
matter at different stages of decomposition and mostly neutral. Rainfall 1600-1800 mm;
salinity and water congestion limit good crop productivity.
(d) Red laterite: Covering Birbhum, Bankura and Midnapore (West) districts. Soils are coarse
in texture, highly drained with honeycomb type of ferruginous concentration at a depth of 15
to 30cm.; erosion prone; acidic in nature; poor available nutrients; average rainfall 1100-
1400mm., low moisture holding capacity and poor nutrient status limit crop productivity.
Zone VII: Eastern Plateau & Hill Region
This region covers Purulia district. Soils are shallow, modulated gravely, coarse textured,
well drained with low water holding capacity, highly susceptible to erosion and acidic.
Rainfall varies from 1100 to 1400mm. which is spread over only three months (mid June to
mid September).
1.3 State Agricultural Plan According to West Bengal Development Report (Planning Commission, GoI., 2010)
3, The
fall in investment in agriculture, particularly public investment, is one of the most
important issues of agricultural development in recent times. But the inadequacy of
statistical information on investments in agriculture is a major limitation to capture the
issue properly. Investments in canal irrigation constitute the major portion of total
investments in agriculture on public accounts. Several documents prepared for the
Eleventh Plan focusing on agriculture pointed out that technological exhaustion was the
major cause for the severe agrarian crisis and poor agricultural growth during the
3 http://planningcommission.nic.in/plans/stateplan/sdr/sdr_wb1909.pdf
4
1990s. Moreover, the intensive cultivation of mono-crop (paddy-wheat sequence) along
with a wide imbalance in NPK ratio in the use of chemical fertilizers affected soil
fertility adversely.
The National Agricultural Development Program or Rashtriya Krishi Vikas Yojana (RKVY)
aims at holistic development of agriculture and allied sectors through all the eligible States of
India. The Agriculture Department, Government of West Bengal is working with the vision
“to achieve sustainable livelihood opportunities for the people through eco-friendly, clean
and value added Agriculture and related activities”.4 The Department‟s website tells about
the vision of "Doubling farmers' income by 2020 by ensuring farmers' access to Skills,
Technologies, Markets and Financial inclusion". The State‟s Agricultural Plan for the XII
Five Year Plan period embodies the following objectives to fulfil this vision5:
1. to ensure quantifiable improvement in production & productivity,
2. to reduce yield gap with focused interventions,
3. to maximize returns to the farmers from Agriculture & Allied sector,
4. to augment marketing interventions and export promotion,
5. to promote competitiveness in Agriculture and Allied Sector and
6. to meet the challenges of Climate Change and evolve mechanisms for effective
drought and flood management.
The crucial agencies and institutions that are operative in the state to fulfil these visions are:
Two State Agricultural Universities and four National Level Institutions are operating
in the field of agricultural extension services
Krishi Vigyan Kendras (KVKs) or Farm Science Centres are specialised institutions
providing vocational training to farmers based on learning through work experience.
There are 16 KVKs in the State functioning under different Agricultural Universities
including Visva-Bharati, Veterinary University, NGOs and ICAR.
There are six centres of Agricultural Technology Management Agency (ATMA) for
facilitating a participatory mode of extension delivery.
NABARD has been instrumental in facilitating the adoption of new/upgraded
technology by farmers/entrepreneurs to promote increased productivity and
production.
Farmers‟ Clubs (FCs) in West Bengal are engaged in supplementing extension
services of State Government Line Departments in the field of Agriculture, Animal
Husbandry, etc.,
The State Agriculture Plan has also recognized few limitations in its present state of affairs.
These are:
Involvement of multiple agencies with overlapping objectives. A well co-ordinated
approach is apparently lacking with different players adopting independent, target
oriented approach.
4 http://rkvy.nic.in/static/SAP/WB/WB.PDF
5 https://wb.gov.in/portal/web/guest/agriculture
5
Limited attempts to understand the farmers‟ location specific needs
Emphasis on technology transfer without fully understanding social/psychological
barriers of target groups (farmers)
One spelt out plan, following the Plan Document in the state, is to develop KVK – NGO –
Farmers‟ Clubs Linkage for effective improvement of income in rural sector. KVKs are the
grass root level extension institutions with mandate for transfer of technology. The KVKs in
general have necessary technical manpower and access to the technologies developed by the
State Agricultural Universities, State Agriculture Departments and other Research Institutions
and necessary physical infrastructure for imparting training and capacity building to the
farmers.
NGOs can play a very effective role in knowledge disseminations through social
mobilization, people‟s involvement and technological interventions. This is clearly
demonstrated in watershed projects. The major gap (with NGOs) is the technical
input/manpower, which can effectively be filled in by the KVKs which have the mandate for
technology transfer but have a few limitations including financial support. An effective
linkage of these three grass root level institutions can be one feasible option in technology
transfer process.
The following recent initiatives of Government of West Bengal might be noted in improving
the performance of agriculture and allied sector in the state:
Task Force of Secretaries on West Bengal Agriculture Commission
Extension Services through Jeebika Sahayaks (Livelihood Associates)
Agriculture related services through NeGP and Agrinet
Training programme for fertilizer dealers and retailers in association with FAI
Focus on Agriculture and Allied sectors through project ATMA
1.4 Rural Non-farm Sector in India and West Bengal The non-farm sector in India is a relatively under-researched component of the rural
economy. In a study, drawing on a large nationally representative household survey for rural
India in 1994, it was indicated that non-farm incomes account for roughly one third of
household income, on average. The study also admitted that the estimate is most likely an
understatement of the importance of non-farm incomes in rural areas, as the calculations were
based on incomes from primary occupations only. The study found that non-farm income
shares vary considerably across states of India, and also across population quintiles. The poor
tend to earn significant shares of total income from casual non-farm wage employment. The
rich earn mainly non-farm incomes from salaried employment. Own enterprise activities
appear to comprise both low-productivity activities and as well-remunerated activities. The
states in which average non-farm income shares are particularly high are Himachal Pradesh,
Tamil Nadu, West Bengal, and the north-east. In these states, non-farm income shares
typically rise with income quintiles (Lanjouw & Shariff 2004).
Analysis of non-farm employment probabilities and earnings found strong evidence of the
importance of education in determining access to non-farm occupations. There is clear
evidence that education improves prospects of finding non-farm employment, and that with
higher levels of education the odds of employment in well-paid, regular non-farm
6
occupations rises. The non-farm sector appears to offer relatively few real opportunities for
women in rural India. A weaker and similar, but still significant, pattern applies to individuals
from scheduled caste and scheduled tribe backgrounds. Not only do these groups typically
possess much lower levels of human capital, but controlling for these assets, they face
additional constraints on employment and earnings in the non-farm sector (Lanjouw &
Shariff, 2004)
Another study on a sample of 2321 rural households in West Bengal shows that wealth and
human capital have a positive impact on the choice of high-return jobs, and low caste workers
are more likely to work in casual, low paying jobs, partly due to their dependence on personal
networks in finding jobs. Notably, no clear evidence of association between social group and
income is found. Occupations are classified into eight categories: (1) self-employed farming,
housewife, and inactive worker, (2) agricultural wage work, (3) local construction, (4) local
factory, (5) local service and self-employment, (6) migratory construction, (7) migratory
factory, and (8) migratory service and self-employment.
It was found that low-caste workers seek jobs primarily through personal networks and
generally find low-return jobs; while upper caste workers generally engage in higher-return
jobs than lower-caste workers, relying on recruitment firms and vocational training centres
more than the low-caste workers do. These findings suggest that providing low-caste people
with information on non-farm job opportunities not available through their personal
networks, and giving them better access to employment support institutions, could increase
their chances of working in the high-return non-farm sectors. Entry barriers faced by
impoverished people may be overcome through education. Additionally, better access to
factory work, to information on non-farm jobs, and to higher human capital could improve
the living standard of the socially and economically disadvantaged people in rural India,
which in turn would lead to poverty reduction (Nakajima et al, 2017).
In another study, longitudinal household survey data collected under the Village Dynamics
Studies in South Asia (VDSA) project by the ICRISAT (Hyderabad), has been used to
explore the role of Non-Farm sector in rural livelihood diversification. The data were
collected for the period 2009 to 2014 in 12 villages across 6 states of India (Andhra Pradesh,
Telangana, Karnataka, Maharashtra, Madhya Pradesh and Gujarat). The study has found that
non- farm income is dominant for all farm households in the selected states where it
contributes 41 - 53 per cent to the household income, except in Gujarat. The share of non-
farm income declines as the landholding-size increases, but at the same time it has a positive
relationship with total income. The preceding statement also justifies higher dependence of
landless labour households as well as smallholders on non-farm income. This suggests that
the non-farm sector and labour market can serve as a leading source of income for landless
and smallholder households. The concern of declining landholding size and dependence of a
large section of population on agriculture, which ultimately is increasing the pie of
economically-vulnerable section of the society, can be overcome by way of giving more
thrust on non-farm sector and promoting rural non-farm enterprises. The access to
agricultural credit and area under irrigation are the crucial factors in determining the
agricultural income of households. The government initiatives towards these in the form of
financial inclusion and Pradhan Mantri Krishi Sinchayee Yojana (PMKSY) might boost the
household income from agriculture and also secure the livelihood of the households‟
dependent on agriculture (Meena et al, 2017).
7
All these studies are drawing similar conclusion regarding the importance of rural non-farm
income and its distribution across social classes and landholding classes. However, the
composition and scale of rural non-farm income has a large variation even within a small
region. A detailed understanding of such earning activities is lacking in the literature, which
needs to be based on primary surveys. This study attempts to fill up this information gap,
which is described in the subsequent sections of this report.
1.5 Doubling of Farmers’ Income: Issues and challenges This study has been undertaken against the backdrop of a recent announcement by the
Government of India regarding some major schemes for uplifting income of the rural
households in the country. The Union Finance Minister, while presenting the General Budget
this year, announced that the Government intends to double the farmers‟ income by
20226. He allotted Rs. 35,984 crore for agriculture and farmers‟ welfare. He said that his
government intends to address issues of optimal utilization of water resources, create new
infrastructure for irrigation, conserve soil fertility with balanced use of fertilizer and provide
connectivity from farm to market.
The Finance Minister also announced Pradhan Mantri Sinchai Yojana (PMSY), to be
implemented in a mission mode to bring another 28.5 lakh hectares of farmland under
irrigation. A dedicated Long Term Irrigation Fund in NABARD with an initial corpus of Rs.
20,000 crore has also been announced in this regard. A similar progrmme for sustainable
management of ground water resources, with an estimated cost of Rs.6000 crores has been
proposed for multilateral funding. He also said that allocations under MGNREGA will be
used for creating at least 5 lakh farm pond and dug-wells in rain fed areas and 10 lakh
compost-pits for organic manure production.
The other major step taken by the Government of India is the announcement of the new
simplified crop insurance scheme, Pradhan Mantri Fasal Bima Yojana (PMFBY). Under the
new scheme that would cost government Rs 8,000-9,000 crore annually, the farmers' crop
insurance premium has been kept at a maximum of 2 per cent for food grains and oilseeds,
and up to 5 per cent for horticulture and cotton crops. The new scheme includes successful
aspects of the previous similar schemes and addresses whatever was lacking in similar earlier
schemes7. The PMFBY has the lowest premium and entails easy usage of technology like
mobile phone, quick assessment of damage and disbursement within a time frame.
From farmers‟ perspective, all these measures are welcome at the first glance. The aim of
achieving „doubled income‟ for farmers, however, leaves some blurred area which needs to
be clarified. Experts are already having different opinion about its achievability8. It is quite
obvious, notwithstanding the debate on whether it is to be measured in real or nominal terms,
that such „doubling of income‟ cannot be achieved uniformly over all agro-climatic zones and
across all social class with a set of uniformly applicable support programmes.
Academic output in the form of commentaries and research articles has started pouring in
since the Government‟s announcement of “Doubling of Farmers‟ Income by 2022” as a target
(Mandal et al, 2017; Singh, 2018). A study in this regard on the coastal region of West
Bengal concluded that one of the key impediments to increase the farmers‟ income in the
state is attributed to small (14%) and marginal (82%) landholdings where an average farmer
6 Press Information Bureau, Government of India; Ministry of Finance ; 29-February-2016
7 Press Information Bureau, Government of India; http://pib.nic.in/newsite/efeatures.aspx?relid=135964
8 Rural Pulse; Issue - XIV, March - April 2016, NABARD
8
operates less than a hectare of land (0.77 ha) (Agricultural Statistics at a Glance,
2016). With these marginal landholdings, farmers produce low volume of marketable surplus,
hence receive low return from their farming business. Therefore, they are incapable to
increase their investment in agriculture. The resource-poor farmers are naturally risk averters
and prefer a lower outcome which is relatively certain to the prospect of a higher return along
with a greater degree of uncertainty. The study also found that for the farmers operating
under different socio-economic conditions, appropriate technologies could be replicated but
„social cloning‟ is beyond the reach of the policy authority. Therefore, enhancing income for
all the farmers across the state would be a challenging task (Mandal et al, 2017).
To face the challenge, the first and foremost requirement is to understand the bottlenecks and
needs of the rural households at the grass root level. It calls for a baseline estimate and
identification of major areas of possible intervention at different agro-climatic zones through
a carefully designed primary survey. This study is an attempt towards that direction.
2. Study objective
The major enabling services to be provided by the Union Government of India (as proclaimed
by the finance minister), implicitly identifies the lack of income growth of the farming sector
with some general set of bottlenecks. This might be true at a macro level. But for efficient
implementation of various assistance schemes, one needs to know about the most binding
issues at local level. Local aspirations and the most important requirements need to be
assessed for implementation of large scale support programmes.
Optimum institutional interventions to enhance farmers‟ income need a set of current
information on farming households as baseline data. Since the state of agriculture and its
relative importance for rural households also varies widely with location, the baseline should
have enough variability in its sample with respect to agro-climatic zones. Such baseline
information is apparently not available for West Bengal as of now.
In the background stated above, the current study had been sponsored by NABARD with the
following objectives:
(i) To estimate the current income level of farm households and its composition
across social and asset classes in four major agro-climatic zones of West Bengal.
(ii) To understand the specific bottlenecks faced by the farm households that are
limiting their opportunities to income enhancement under different agro-climatic
zones
(iii) To understand the level of diversification in crop choice as well as allied, off farm
and non-farm activities of rural households along with the constraints, possibilities
and supports required for such diversification.
(iv) Estimation of farm economics and financial requirement (including bank credit)
to double farm income (by 2022) and efficient strategies to meet their financial
requirement.
9
(v) The extent of assistance from Centre/State/PRIs/NGOs being received by the farm
households and hindrances in getting the benefits, if any.
(vi) To understand from farmer’s point of view, under different circumstances, the
most warranted form and quantity of supports / facilities / policy that could enable
them to double their income by 2022.
(vii) Designing a state specific strategy for doubling the farmers’ income taking into
account the farmers’ need and constraints faced in the state.
(viii) Recommend sector specific interventions (especially on irrigation, soil health,
warehousing, cold chains, value addition, marketing, allied activities, non- farm/off
farm activities, wage employment etc.)
(ix) Recommend collaboration and partnership among stakeholders, channel
partners, their proposed engagements and convergence plan.
The study has been carried out with an intensive field survey of sample household to address
the specific objectives listed above. The study commenced on 1st July, 2017 and had a
targeted completion time of six months from the date of commencement. This report is
prepared with the information collected from the field during August-November, 2017.
The reliability of such a study crucially depends on the sampling scheme and the types of
information collected through the survey instrument. The following sections are arranged to
provide a detailed description of the sampling procedure, a brief description of the survey
questionnaire, a detailed description of survey findings and a follow up discussion on the
findings. Appropriate policy suggestions are made based on the survey findings at the end of
this report.
3. Sample design
The set of objectives of this study required a very careful selection of rural households across
the state of West Bengal. The time and budget allocation allowed for only 200 sample
households from each agro-climatic zone in the state, which is a very small sample compared
to the heterogeneity in the population within each zone. So, utmost care had been taken to
ensure enough variability in the sample households in this sampling scheme.
The variations in the practices and earning possibilities of rural households are assumed to be
affected by the following crucial aspects:
Geographical location (agro-climatic zones)
Irrigation infrastructure
Infrastructure in terms of transport/communication
Proximity to urban centres
Households‟ land endowment
Keeping in view the requirement of ensuring variability on the above counts, respondent
selection had to be multi-stage. Following is the details of stages through which selections
were made in this study to arrive at the final survey sample.
10
3.1 Selection of sample districts
In the first stage, according to the study condition stipulated by NABARD, one district was
chosen from each of the major agro-climatic zones in West Bengal. There are six such zones
(Sub-regions, as described in section 1.2 before) in West Bengal. The distribution of districts
across them is shown in the Table-2.
Table 2: Distribution of districts of West Bengal across agro-climatic zones
Agro-climatic zones Districts (by the main soil type)
Coastal saline zone South 24 Parganas
Gangetic alluvial zone Burdwan, Hooghly, Howrah, Murshidabad, Nadia, North 24
Parganas
Undulating red lateritic zone Bankura, Purulia, Birbhum, West Midnapore
Vindhya alluvial zone: Malda, Dakshin Dinajpur
Terai alluvial zone Coochbehar, Jalpaiguri9, Uttar Dinajpur
Northern Hilly zone Darjeeling
Also, at most four districts and hence four such zones could be covered for the state
following the study mandate. The four districts that are covered in this study are indicated in
bold fonts in the table. The choice of the districts was made keeping in view its importance in
absolute geographical size and population within each major agro-climatic zone. Each one of
the selected district (Bankura, Burdwan, Jalpaiguri and South 24 Parganas) is the largest in
population and geographical area among its peers within the same agro-climatic zone. Two
such zones (Northern Hilly and Vindhya alluvial) had been left out of the sample following
the same criteria (i.e., they are the smallest in terms of population and geographical
coverage). Moreover, Bankura is the Backward District in terms of agricultural performance,
which was a mandated selection criterion in this study. The location of the sample districts in
the state is shown in Appendix-1.
3.2 Selection of sample blocks
The district selection ensured representation of four major and most populous agro-climatic
zones of West Bengal. In the second stage, three CD blocks had been selected from each of
the four sample districts. Such blocks were selected keeping in mind the variability in the
other major issue of irrigation. There can be three broad types of irrigation status:
(i) Irrigation by lifting of ground water (using shallow / submersible pump sets)
(ii) Irrigation by lifting/channelizing surface water (canal/ pond irrigation)
(iii) No irrigation (purely rain fed agriculture)
Blocks are expected to show enough variation in the major form of irrigation across them. It
is also understood that within an agro-climatic zone (here a district), variation in irrigation
facility has a close relation with cropping diversity. Production figures of all major crops are
9 This district was later split into two during the survey implementation time. In this report, “jalpaiguri‟ includes
both of the new districts – „Jalpaiguri‟ and „Alipurduar‟.
11
available from secondary sources at block level. So, blocks are selected within a district
according to their cropping diversity as a proxy to variability in irrigation facilities as well.
The following table provides an idea of the number of blocks, and villages therein, within
each of the selected districts.
Table 3: Blocks and villages across survey districts
District No. of
Blocks
No. of
Villages
Bankura 22 3,823
Barddhaman 31 2,502
Jalpaiguri 13 733
South 24 Parganas 29 2,044
Total 95 9,102
Source: Village Amenities, Census 2011
Latest official data were obtained at block level10
on the area cultivated (in hectare) under
Aus paddy, Aman paddy, Boro paddy, Wheat, Maize, Jute, Musur, Maskalai, Khesari, Gram,
Mustard, Til, Potato and Sugarcane for each of the four selected districts The crop
diversification index was calculated following the well accepted formula given below:
Herfindahl Index (𝐻𝐼) = 𝑆𝑖2𝑛
𝑖=1 , where 𝑆𝑖 implies the share of the i-th crop area
in total crop area of the block.
Cropping Diversity Index (DI) = 1- HI
The index, by its construction, lies between the closed interval (0,1). We divided the range of
DI into three equal parts and categorized all the blocks under a district as of High, Medium
and Low according to their calculated DI.
For each district, we had chosen three blocks - one from each DI category. In doing so, we
also ensured the maximum variation in the major soil types that are available in that district.
Also proximity to urban centres and the railway transport facilities are considered (using
Google map) in block selection so that maximum diversity in those counts is also ensured.
The final selection of blocks is shown in Table-4:
10
Source: District Statistical Handbooks, 2014
12
Table 4: Sample CD Blocks in four sample districts
District High diversity Medium Diversity Low Diversity
Bankura Patrasayer Onda Chhatna
Burdwan Ausgram – I Kalna – II Salanpur
Jalpaiguri Alipurduar-II Rajganj Moynaguri
South 24 Parganas Diamond Harbour - I Mathurapur - I Patharpratima
Source: Author’s calculation using information from District Census Handbooks
3.3 Selection of sample villages For selection of villages, there was no ready information from secondary sources. We
depended on the Assistant Director of Agriculture (ADA) of each sample block and
conducted Focus Group Discussions (FGD) with him and his Krishi Pryukti Sahayaks
(KPSs). In taking decisions on the villages to survey, in FGDs with ADAs, maximum
variation across villages (within that block) were ensured with respect to:
The main crop
Irrigation status
Remoteness (transportation facilities)
The villages were suggested by the ADAs under his/her block from his/her personal
experiences about the state of their current agriculture so that the villages are different from
each other in terms of the three aspects mentioned above. From each block, at least three
villages were selected with one block (the largest one) contributing to an additional village.
So, a total of 10 villages from three blocks in each district were selected. The main features
of these selected villages, noted down from the opinion of the ADAs, are provided at the end
of this report (Appendix-2).
3.4 Selection of sample households The ADAs and KPSs provided some key-person‟s contact for each of the suggested villages
who had been hired later-on to enlist all the households in that village along with their current
landholding status. In this way, the Sampling Frame of households for the 40 villages in four
districts had been prepared for primary survey.
The study had a survey target of 800 sample households, taking 200 from each of the four
districts. In each district, 10 villages were selected by the procedure described above. So, 20
households were to be selected from each of these villages.
The landholding distributions were found to vary significantly across the 40 villages. A
uniform landholding stratification across them would not have ensured enough variation in
household asset (land) holding within each village. So, landholding stratum had been
decided for each village separately. For each of them, from the full list of households, the
„landless‟ category had been separated out first. Then, from the landholding distribution of
the remaining households, quartiles had been calculated. This way, each village-list was
divided into five land-classes. Four households from each land stratum were selected
13
randomly using computer generated random numbers. So, a total of 20 households were
selected from each village as a stratified random sample.
The sampling procedure mentioned above resulted in a target list of 800 households (4
districts x 10 villages x 20 households). However, while sending the enumerators to the field,
a list of replacement households (in case the original target household is unwilling / absent)
were also prepared so that replacements are also random within the corresponding strata. In
actual survey, some of these replacements were actually surveyed while the original one had
also turned up eventually. Hence a little more than the target surveys was accomplished. The
results presented in this study are based on a total sample size of 809 households.
3.5 Brief description of information collected In this study, information was collected through a carefully designed modular instrument
with close-ended and pre-coded options provided against most of the questions. Only
regarding the problems faced by the rural households in availing assistance schemes and in
eliciting their income enhancement / diversification plans, prior codes could not be provided.
The survey instrument was developed with inputs from FGDs with ADAs during July, 2017.
The instrument was pre-tested for around 20 households in three different villages in the first
half of August, 2017.
The questionnaire was developed in a modular structure. Following is a brief description of
the modules and their contents:
Module A: Household member profile and standard household level information
Module B: Plot wise and season wise details of agriculture with irrigation sources.
Module C: Details of allied and non-farm activities by members of the households
Module D: Awareness regarding government sponsored assistance programmes
Module E: households‟ current credit profile and usage
Module F: Description of livestock holding and earning from livestock
Module G: Earning diversification plans of the households and required assistance for it
Module H: Details of fishing and related activities and expansion plans
Module I: Details of plantation crops
Module J: Experience and opinion on Soil test, KCC, PMFBY, PMSY etc.
4. Study findings
The results obtained from analysis of the full set of survey data is described in this section
with the help of summary statistics and charts. These are arranged under some broad sub-
sections as described below.
4.1 Household profile across survey districts It is necessary to have an idea of the broad socio-economic profile of the sample households
across the four survey districts. Table-5 describes the distribution of household size, age, sex
and education level of the household head across the four survey districts. The table shows
that Bankura district (mostly Lateritic zone) is having a relatively bigger household size and a
marginally bigger average landholding. Also, the average number of years of schooling of the
household head is lowest for this district. This is in conformity with the conventional idea
that the Lateritic zone is relatively backward and it might need a bigger household size for
their sustenance in a rain-fed area, since more household members needed to be engaged in
multiple earning avenues.
14
Table 5: Sample households' broad characteristics across survey districts
District & Agro- Climatic zone
No of sample
HH
No of HH with Female Head
Average HH Size
Average years of
schooling of HH Head
Average age of HH Head
(Years)
Average Land
holding (Hectare)
Bankura (Mostly Lateritic, partly Gangetic Alluvilal)
200 6 5.1 4.8 50.0 0.43
Burdwan (Mostly Gangetic Alluvilal, partly Lateritic)
206 17 4.6 6.1 50.8 0.42
Jalpaiguri (Terai Alluvial)
200 6 4.7 5.4 48.0 0.39
South 24 Parganas (Coastal Saline)
203 10 4.8 5.6 50.1 0.24
Total 809
[Source: Primary Survey]
It is also seen from Table-5 that the average household landholding is much lower in the
South 24 Parganas district. This is also in conformity with secondary information since this
district has the largest population density among all the four survey districts. Another
interesting feature in this table is that the average landholding size is indeed very low across
all the districts. This confirms the prevalence of landless and marginal farmers in the state of
West Bengal as a whole.
Other intricate details of household composition and endowments, though partially collected,
are not being reported here as they might not be very useful for this particular report.
However, it might be interesting to have a glimpse of the penetration of banking habits and
the availability of Aadhar number among the survey population, since most of the
government assistance programmes in India these days are channelized through banks linked
with the beneficiaries‟ Aadhar number. This is described in Table-6.
Table 6: Prevalence of banking habits and availability of Aadhar numbers
Bankura (Lateritic/ Gangetic Alluvial)
Burdwan (Gangetic Alluvial/ Lateritic
Jalpaiguri (Terai
Alluvial)
South 24 Parganas (Coastal Saline)
Aggregate
No. of sample households 200 206 200 203 809
Total number of members in sample HHs 1026 950 934 966 3876
Total no. of Adult Member (age>=18 yrs) 729 714 686 703 2832
No. of HHs having any Bank Account 191 200 199 196 786
% of Adults having any Bank Account 68.9 75.1 80.3 70.3 73.6
% of household members having Aadhar 90.7 90.7 92.6 90.5 91.1
[Source: Primary Survey]
15
It is seen that almost three quarter of the adult population in these districts have at least one
bank account (including recently opened Jandhan accounts) and over 90 percent of the
sample population have Aadhar numbers. While the distribution of Aadhar numbers is fairly
comparable across survey districts, the banking habits are not that homogeneous across them.
Jalpaiguri (Terai alluvial) has more banking penetration and Bankura (Lateritic) is lagging the
most on this count.
Turning to rural livelihood and income diversification, the first glimpse of the distribution
can be obtained by classifying the different reported earning activities into some broad
categories. Table-7 describes the relative distribution such broad categories across the survey
districts.
Table 7: Relative importance of earning activities across survey districts
Broad categories of earning activities Bankura (Lateritic/ Gangetic Alluvial)
Burdwan (Gangetic Alluvial/ Lateritic
Jalpaiguri (Terai
Alluvial)
South 24 Parganas (Coastal Saline)
Aggregate
No. of Survey HH 200 206 200 203 809
Percentage of sample household reported to be engaged
Own Agriculture 74.0 61.7 79.0 59.6 68.5
Fishing and pisciculture 2.0 2.9 0.5 7.9 2.7
Own small tea plantations 0.0 0.0 19.0 0.0 4.7
Livestock earning 5.5 1.0 4.0 1.5 2.7
Farm Labour 33.5 29.1 21.5 21.2 26.3
Non-Farm Labour 21.0 18.0 20.0 22.7 20.4
Agro-related business 3.0 5.3 5.5 4.9 4.7
Other Business activities 27.0 26.2 34.5 36.5 31.0
Other Non-Farm activities 35.0 56.8 52.0 46.8 47.7
[Source: Primary Survey]
It might be noted that the percentage of households across different activities adds up to more
than 100 percent for each district. This is members of a household are found to be generally
engaged in more than one activity in different seasons. Own cultivation is found to be the
predominant activity across all the districts as expected. However, this is lowest in South 24
Parganas (Coastal saline zone) which is compatible with the fact that this district has the
lowest average landholding per household. It is to be noted that the percentages had been
calculated in each district using all sample households within it. So, the landless had been
automatically absent from „own agriculture‟ but is largely present in the „farm labour‟
earning category.
Smaller percentage of „own agriculture‟ in Coastal saline zone is partly compensated by
„fishing and pisciculture‟ which is reported by a significantly higher percentage of sample
households compared to other district. It is expected as coastal fishing is an important activity
16
for many households (especially landless) in this district, the scope of which is absent in other
districts.
The agricultural backwardness of Bankura (mostly Lateritic zone) can be detected from the
fact that a smaller percentage of households there are engaged in agro-related business
compared to other districts. This is explained by the fact that such business scope is more for
vegetable cultivation and winter crops, which are more prevalent in other agriculturally
forward zones. The district, however, seems to compensate the scarcity of agricultural
income by livestock earning, as the percentage of households reported such earning is highest
among the four districts.
Jalpaiguri (Terai Alluvial) stands out as the one which has a significant earning from small
tea plantations, which thrived in this zone for the last two decades. Our later analysis will
show that this additional opportunity provided by the soil characteristics has made the
agricultural income quite high in that zone.
Other important finding from Table-7 is that for all districts, there is significant presence of
non-agro-related businesses and other non-farm activities. Close to half of the households had
reported some form of non-farm income across them. Section-1 previously identified that
non-farm income is a significant component of rural earning in West Bengal due to
dominance of marginal and small holders. Households fail to sustain themselves depending
on agriculture alone. Rural earning diversification is, hence, quite large in West Bengal. A
more detailed analysis of these non-farm activities might be of interest here.
Table 8: Composition of other non-farm activities reported by sample households
Broad categories of
Other Non-farm earning activities
Bankura (Lateritic/ Gangetic Alluvial)
Burdwan (Gangetic Alluvial/ Lateritic
Jalpaiguri (Terai
Alluvial)
South 24 Parganas (Coastal Saline)
No. of HHs engaged 70 117 104 95
Percentage of sample household reported to be engaged
Salaried 27 50 24 33
Migrant Labour 23 9 19 33
MGNREG 19 36 61 29
Self Employed 16 15 9 14
Other Activities 79 43 54 64
[Source: Primary Survey]
While the questionnaire included codes for many different earning activities, reporting all of
them in a single table might make the message blurred. Table-8 decomposed the non-farm
activities into few broad categories. The percentages shown in Table-8 are calculated out of
the households which reported at least one of these non-farm activities (including secondary
sources of earning as well). Again they sum up to more than 100 percent because households
might have been engaged in more than one type of non-farm activities.
We can see some interesting points here. The district Burdwan (mostly Gangetic Alluvial)
has a very high percentage of salaried income (including both private and government) while
17
very low presence of migrant labour. This is in conformity with the common idea that the
district‟s average education level is high. This is also corroborated by Table-5 where the
average number for years of schooling of the household head is found to be highest in this
district. The low presence of migrant labour in the same district tells us that availability of
secured local income restricts the outflow of migrant labour. South 24 Parganas (Coastal
Saline) shows a prevalence of migrant labour in survey households. One can correlate this
phenomenon with the relatively lower land endowment and high population density in that
zone.
The primary survey had collected the details of all non-farm activities of all the members of
the sample households and estimated their annual earnings from it. However, the data
revealed that the activities are too many in nature and when distributed over different agro-
climatic zones, the frequency of each specific activity within a single zone is too few to
convey any statistically meaningful estimate. Hence income estimates from the non-farm
sector has been carried out taking all such activities together. The detailed frequency
distribution of these activities across the four agro-climatic zones, however, is provided in
Appendix-3 of this report.
The composition and magnitude of most of these non-farm activities are determined by the
market conditions and the overall local and regional economic scenario. However, one of
them stands out as a direct intervention by the government. The „100 days work programme‟
(MGNREGA), as is widely accepted already, has brought significant changes in the rural
livelihood dynamics. The intensity of its implementation depends on local administrative
efficiency, local political situation and also on the local resource constraints. We wanted to
look into the performance of MGNREGA across survey districts and also the availability of
Jandhan accounts with the „Job Card‟ holders. As Table-8 has already shown, the
implementation of this income generation scheme is found to have a wide variation across
districts. We needed to know whether it is because of lack of job-seekers or because of lack
of job-creation. Table-9 provides some interesting insight in this regard.
Table 9: Availability of Job Card, Jandhan account and work under MGNREGA
No of
sample HH
HHs having Job card for MGNREGA
Got MGNREGA work within last one year Avg. Days
of work (last yr)
% of HHs having Jandhan
account No Yes No Yes
Bankura (Lateritic / Gangetic Alluvilal)
200 54 146 133 13 21.3 18.8
Burdwan (Gangetic Alluvilal / Lateritic)
206 53 153 111 42 28.7 10.0
Jalpaiguri (Terai Alluvial)
200 41 159 96 63 35.3 15.9
South 24 Parganas (Coastal Saline)
203 68 135 108 28 33.7 24.7
Total 809 216 593 448 146 29.8 17.4
[Source: Primary Survey]
18
It is seen that the number of job card holders (might be considered as job-seekers) for the
comparable number of households is less in South 24 parganas. This might be due to the fact
that this district has the largest concentration of migrant workers (Table-8) who don‟t stay in
their village for most of the time in a year. But it is clear that though there is enough number
of job-card holders, the availability of MGNREG jobs is lowest in Bankura both in terms of
number of persons getting it and the average number of days per year for which it was
availed (in 2017). This keeps open the possibility that there is enough room for job-creation
through this channel in this rain-fed Lateritic zone. Due to lack of agricultural options in a
conventional way, there might have been a dearth of work plans in MGNREG scheme
coming spontaneously from local bodies in this district.
The field observation suggests that there is good scope for scaling up Integrated Water
Management Projects (IWMP) in Lateritic zone (Bankura, Burdwan) as demonstrated by
some local enterprising associations who could avail them through the patronization of
Assistant Directors of Agriculture (ADAs). Such projects need a lot of manual work in
creating check-dams and dug-wells. Usually the cost of these infrastructures is accounted to
the project itself, whereas MGNREGA provisions could have been used. This finding
suggests that there is good scope of integration of these two projects for the Lateritic zone.
Lastly, as a part of household endowments, it is imperative to have a look at the livestock
holding scenario across the agro-climatic zones. The survey enumerated the possession of
livestock by the respondent households, which is summarized across zones in Table-10.
Table 10: Distribution of livestock across agro-climatic zones
Survey District & zone
Average number of livestock per sample household
Cow / Buffalo
Goat Pig Chicken Duck
Bankura (Lateritic / Gangetic Alluvilal)
2.6 0.9 0.00 1.3 0.6
Burdwan (Gangetic Alluvilal / Lateritic)
1.3 1.2 0.01 1.2 0.8
Jalpaiguri (Terai Alluvial)
1.9 0.9 0.00 1.9 0.3
South 24 Parganas (Coastal Saline)
1.0 0.4 0.00 1.4 0.4
Aggregate 1.70 0.85 0.00 1.45 0.51
[Source: Primary Survey]
It is seen that the average number of cows and buffalos is more in Bankura (mainly Lateritic)
which has also reported the maximum percentage of livestock earning activities (Table-7). It
seems that households in this zone are trying to make up for their lack of farming opportunity
through livestock rearing more intensively. The assistance schemes for livestock (free
distribution of livestock and fodder) need to be more concentrated towards this zone as the
households have a better ongoing practice in livestock maintenance.
19
4.2 Cropping pattern and livestock across socio-economic classes One of the prime objectives of this study is to estimate the existing household income level
and its composition across different agro-climatic zones, landholding classes and social
classes. Information collected on these aspects are summarized and presented in this section.
The respondents are categorized on three different aspects separately and the tables and
charts are presented with such categorizations. The categories are specified below:
Table 11: Definition of different categories of survey sample
Type of categorization Category description
Agro-Climatic Zones
1. Gangetic Alluvial : Blocks Ausgram-I & Kalna-II from Burdwan
district; Block Patrasayar from Bankura district11
2. Terai Alluvial : All blocks of Jalpaiguri district
3. Lateritic : Blocks Chhatna & Onda of Bankura district
and Block Salanpur from Burdwan district
4. Coastal Saline: All Blocks of South 24 Parganas district.
Land-holding class
Landless : 0 Hectare
Marginal farmer : 0- 1 Hectare
Small farmer : 1-2 Hectare
Semi-medium farmer: 2-4 Hectare
Medium: 4-10 Hectare
Large: > 10 Hectare
Social class This was done through the household‟s caste identity involving four
categories: 1. SC 2.ST 3.OBC and 4. General
The categorization of landholding class had been done following the official definition of
agricultural size classes as followed in all official estimates in India. However, it is to be
noted that agriculture in West Bengal is characterized by overwhelming presence of marginal
11
There has been some overlap in soil types and district boundaries. In the sampling scheme, Burdwan was
considered Gangetic Alluvial and Bankura as Lateritic. But after Block selections were made based on crop
diversification, it was found that one selected block of Bankura falls under Gangetic Alluvial while one selected
block of Burdwan falls under Lateritic soil type.
20
and small farmers. In our survey also, it turned out that landless, marginal and small farmers
are dominating the sample. There are few households which fall under the semi-medium
category. There is only one sample household which can be characterised as „medium‟. The
averages calculated on the basis of such a small sample size is not statistically valid. So, that
single household has been discarded from the analysis in this section. No „large‟ farmer was
found in our survey sample.
Before presenting the income estimates and its composition across these categories, an
overview of livestock endowments, irrigation status and cropping pattern might be of interest.
These will be useful to provide an idea about the basis on which farm income and income
from agriculture-allied activities are derived. The livestock holding scenario has already been
described across districts. But livestock holding generally has a relation with agricultural
landholding as well. Table-12 described the livestock composition across different
landholding classes over the whole sample.
Table 12: Livestock distribution across land holding classes
Landholding Class
Average number of livestock per sample household
Cow/Buffalo Goat Pig Chicken Duck
Landless 0.8 0.8 0.01 1.2 0.4
Marginal 2.0 0.9 0.00 1.6 0.5
Small 3.3 0.7 0.00 1.7 1.0
Semi-Medium 3.9 0.4 0.00 2.0 0.2
Aggregate 1.70 0.85 0.00 1.45 0.51
[Source: Primary Survey]
The above table clearly shows that the cow-holding is positively related with agricultural
land, but that of medium livestock (goat) has an inverse relation with it. One can conclude
that landless and small holders try to obtain income from goats as they don‟t get sufficient
fodder from own agriculture to maintain their cows/buffalos. For chicken and duck, the
distribution doesn‟t show any relation with households‟ landholding. This table implies that
distribution of livestock and fodder, if done with the aim of helping the lowly endowed rural
households, should be done in the form of goats and not cows/buffalos.
It is common knowledge that farm income crucially depends on the availability of irrigation
water. Availability of irrigation increases the gross acreage of a farm household and hence
enhances its farm income significantly. The survey listed the different sources of irrigation
for the farming households in the sample (including own land and leased-in-land). The
cropping intensity for each household is calculated as the number of crops they raised over
the last one year (from 1 to 3). The average cropping intensity has been calculated (averaged
over households) for each type of irrigation sources. A total of 537 households (out of a total
of 809) had their own cultivation within last one year with unambiguous responses regarding
sources of irrigation. The distribution of such households and the corresponding average
21
cropping intensities across different irrigation sources is described in Table-13. The table
helps in understanding that ground water is the most reliable irrigation source for raising
crops in winter and summer. Availability of ground water irrigation (using shallow and
submersible) along with pond and canal lifting irrigation enables the farmers to raise almost
three crops per year (cropping intensity of 2.8 or above). However, pond and canal lifting
irrigation also does not lag far behind. When such facilities are available, farmers can
certainly raise two crops and in almost half of the cases can raise three crops per years as
well. Though ground water is the most assured irrigation source, intensification of ground
water use has serious ecological implication in the long run. The table helps in understanding
that pond irrigation (rain water harvesting) and canal irrigation (surface water management)
can be good alternatives to ground water for irrigation. The table also highlights the fact that
irrigation is an important input for agriculture, as rain fed (no irrigation) plots are lagging far
behind in cropping intensity compared to their irrigated counterparts. Any intervention in
enhancing farm income has to do something about irrigation infrastructure.
Table 13: Cropping intensity across different types of irrigation and across zones
Average Number of crops per year
Irrigation Type Gangetic
Alluvial
Terai
Alluvial Lateritic
Coastal
Saline Aggregate
Only ground water (shallow/submersible) 2.0 1.9 2.0 1.6 1.9
Only pond water (lift irrigation) 1.5 1.8 1.3 1.8 1.6
Only canal water (lift irrigation) 1.9 1.5 1.2 1.9 1.7
Ground water and Pond water 2.1 2.2 1.2 2.2 2.1
Ground water and canal water 2.3 No Obs No Obs No Obs 2.3
No Irrigation 1.4 1.4 1.1 1.3 1.3
Aggregate 1.8 1.7 1.3 1.5 1.6
[Source: Primary Survey]
Before presenting the estimates of farm income, it is important to get an idea about the
cropping pattern across different agro-climatic zones. It is observed that paddy is the
predominant crop in monsoon season barring one or two households in all agro-climatic
zones. There is no variation in this phenomenon in West Bengal and hence it is not
interesting as information. All other major crops that are reported to have been cultivated
within last one year by the respondent households have been identified and some of them
have been classified under broad categories like pulses, oilseeds and vegetables. The
percentage of sample households that are reported to have cultivated them is shown in Table-
14. Calculation of percentages was done on the basis of the total number of sample
households (first row in Table-14) including the landless. This is because, it is often
observed, that the landless households leases-in small plots in the winter or summer from the
large owners and can make profit out of vegetable and other cultivations after putting
intensive family labour, which is otherwise not that profitable for large landowners who
usually hire all their labour input.
22
Table-14 shows that potato (winter) and summer paddy are the most important crops apart
from monsoon paddy in the Gangetic Alluvial zone. Oilseeds and vegetables come next in
ranking in this zone. For Terai Alluvial zone vegetables and potato in winter and jute in
summer rank high. For Lateritic zone, there is no significant crop in summer but a third of the
households reported some vegetable cultivation in winter. For the coastal saline zone,
vegetables and pulses are the two important crops after monsoon paddy.
The cropping pattern also indicates that the Terai Alluvial zone is the most diverse in farming
activities. It turns out that this zone reaps the highest farm income for its soil quality and
water availability sources from innumerable Himalayan rivers flowing through it. Contrary to
popular belief, the survey finds that Terai Alluvial zone scores over Gangetic Alluvial zone in
terms of agricultural prosperity and diversity. This is added by the fact that certain blocks in
the zone has a soil type appropriate for tea cultivation and a significant number of landed
households are having small tea plantations. This is not reported in Table-14, as tea is a
multi-year crop and cannot be associated with any season.
Table 14: Cropping pattern across different agro-climatic zones
Agro climatic Zones
Gangetic Alluvial Terai Alluvial Lateritic Coastal Saline
No. of sample HH 224 200 182 203
Percentage
of sample
HHs
producing
Summer Paddy 30.4 6.5 7.7 11.3
Winter Paddy 1.8 0.5 0.0 1.0
Wheat 0.9 1.5 1.6 11.8
Maize 0.0 11.5 0.0 0.0
Jute 7.1 35.0 0.0 0.0
Oilseed 15.6 10.0 19.8 6.4
Pulses 0.0 0.0 1.1 20.2
Potato 46.4 32.0 13.7 9.4
Vegetables 19.2 57.0 39.6 50.2
[Source: Primary Survey]
23
4.3 Household earning and its composition
One of the most important objectives of this study is to estimate the income of the rural
households across different agro-climatic zones and its broad compositions. The survey
collected information on all sources of earning from each of the sample households and
calculated annual income from these sources across all seasons. In doing so, income from
agriculture has been calculated by deducting the cost from production and sale. Where
household inputs were used and the production was not sold (self consumption by
households), the values of inputs and output have been imputed by corresponding average
prices obtained from the same village for respective inputs and output.
One word of caution is important here. Rural India as a whole is getting lots of assistance in
different forms under different central and state government schemes. The villagers are
always motivated to respond in a pre-determined way so as to present themselves as poor.
The survey was conducted by repeated clarification to the respondents that they are not going
to get any immediate benefit from their responses as the report will be totally anonymous
about respondents‟ identity. Still, it is understood, that the embedded idea inside their mind
barred them from revealing all of their earning sources. The estimates presented here might
be an underestimation in this count. However, assuming that this phenomenon is universal
across different agro-climatic zones, one can consider that the extent of under-reporting is the
same across the zones. Under this assumption, the comparability of the zonal averages stand
out as reliable. Also, the percentage shares of earning from diverse activities are reliable if we
assume that under-reporting is not systematic for any particular set of activities.
From the collected detailed information, earning sources had been categorized under few
broad heads as follows:
Agricultural earning in Monsoon (farm-income)
Agricultural earning in Winter by own cultivation (farm-income)
Agricultural earning in Summer by own cultivation (farm-income)
Earning from plantation crops by own cultivation (tea and betel leaf) (farm-
income)
Earning from agriculture-related activities like farm labour in crops and
plantations, livestock earning, earning from pisciculture, earning from ago-related
business (Allied activities)
Other Non-farm activities (all other remaining earning sources)
The following table describes the survey estimates of average net income of the sample
households across the four agro-climatic zones. In calculating the „net income from
agriculture‟, input costs had been deducted from the gross earning including the imputed
costs of own inputs like family labour. The zonal averages had been calculated including all
landholding classes and social classes. As was hinted previously, the Terai Alluvial zone
shows the highest average income for rural households. However, it might be noted that a
significant part of it comes from small tea plantations that dot many of the blocks in that
24
zone. As expected, the rain fed Lateritic zone reported the lowest earning in absolute terms,
but the lowest share of agricultural earning is reported by the Coastal saline zone. This is not
contradictory as the Coastal saline zone has the largest population density, lowest average
landholding and highest migrant labour concentration. It might also be noted that the lower
earning in Lateritic zones comes from highest average landholding and household size
compared to other zones. So, if the earnings are normalized by landholding and household
size, the Lateritic zone‟s position in the table will recede further. The low agricultural earning
share in Coastal saline zone seems to be partly compensated by betel leaf plantations and
income from non-farm sector.
Table 15: Detailed composition of HH earning across agro-climatic zones
Gangetic
Alluvial
Terai
Alluvial Lateritic
Coastal
Saline
Avg. Annual income (all sources) (Rs.)
(Coefficient of Variation)
30,578
(2.1) 58,132
(2.3) 28,890
(2.9) 29,833
(2.1)
Avg. HH Size 4.44 4.67 5.4 4.76
Avg. Land Holdings (Hectare) 0.4 0.39 0.45 0.24
% of Income Earned
Monsoon Agriculture 33.3 11.3 29.6 16.1
Winter agriculture 8.9 14.3 5.1 9.7
Summer Agriculture 11.1 11.1 6.4 5.5
Total earning from Agriculture (%) 53.3 36.7 41.1 31.3
Plantation
Earning from tea plantations (%) 0 15.8 0 0
Earning from betel leaf plantations (%) 0 0 0 6.3
Earning from Allied activities (%) 14.2 15.3 14.6 14.8
Earning from other Non-Farm activities
(%) 32.5 32.2 44.3 47.6
[Source: Primary Survey]
Table-15 reports the percentage shares of earning from a detailed classification of sources. A
simpler comparison of earning from broad sources across agro-climatic zones is facilitated by
the following figure.
25
Figure 2: Composition of average household income across agro-climatic zones
The zonal averages provided in the previous discussion somewhat blurred the extent of
inequality across households within each zone. The extent of inequality in income within
each zone is indicted by the high Coefficient of Variation as indicated in the corresponding
parenthesis. Such variations are resulting primarily from the differences in land endowments
among the households within each zone. So, it is important to understand the income
composition across different landholding class. This is more so, as “doubling of farmers‟
income” target should need interventions prioritized for the small holders, especially in a
state like West Bengal where they are the majority. Table-16 provides similar information,
but across different landholding classes taking all the zones together.
Table 16: Detailed composition of HH earning across landholding classes
Landless
Margi-
nal Small
Semi-
medium
Avg. Annual income (all sources) (Rs.) 23,017 39,429 89,485 89,378
Avg. HH Size 4.19 4.77 6.97 6.78
Avg. Land Holdings (Hectare) 0 0.36 1.35 2.43
% of
Income
Earned
Monsoon Agriculture 7 23 27 51
Winter agriculture 6 13 12 5
Summer Agriculture 3 10 13 5
Total earning from Agriculture (%) 17 46 52 61
Planta-
tions
Earning from tea plantations (%) 0 4 17 0
Earning from betel leaf plantations (%) 0 2 0 0
Earning from Allied activities (%) 28 12 7 24
Earning from other Non-Farm activities
(%) 55 36 24 13
[Source: Primary Survey]
0
5
10
15
20
25
30
35
Gangetic Alluvial Terrai Alluvial Lateritic Coastal SalineAn
nu
al
earn
ing
( '000 R
s)
Agro-climatic zones
Farm Income Income from Allied Activities Other Non-farm Income
26
The data revealed in Table-16 indicates that while the landless households are surviving with
less than Rs. 2000 per month, the marginal landholders are earning around Rs. 3500 per
month and the small and medium farmers are earning around Rs. 7500 per month from all
sources. The Table is in conformity with the expectation that larger landholding is associated
with a larger family size and greater share of agriculture in total household earning. They in
turn, have lesser proportion of income coming from „other non-farm‟ activities.
One interesting phenomenon comes out regarding earning from small tea plantations. This is
only available in Terai Aluuvial zone (Jalpaiguri district). As already shown in Table-14, as
much as 15.8 percent of average income comes from small tea plantations in this zone.
Table-16 shows that much of this income is being enjoyed by the large landowners. From the
field discussions, it was revealed that small-holders cannot avail the benefit of tea-earning as
converting their small land (sometimes only one or two plots) into tea plantations means
sacrificing their agricultural return for at least three years. Many of them expressed
willingness to convert their land if institutional support is provided to them for such
conversions. It calls for arrangement of longer term credit where repayment can start only
after three years.
Lastly, it would also be interesting to see how such earning composition changes across
different social class. This is described in Table-17. It is observed that Scheduled Tribes are
relatively worse off in terms of their absolute value of annual earning, compared to the other
social classes. It is interesting to note that average annual income of SC, OBC and General
castes are fairly comparable in terms of their magnitude and composition. It states that, at
least in West Bengal, government sponsored assistance programmes for rural income
generation need no quota for SC and OBC section, though there might be a need for special
support for ST category.
Table 17: Detailed composition of HH earning across social classes
SC ST OBC General
Avg. Annual income (all sources) (Rs.) 37,314 22,930 37,774 38,913
Avg. HH Size 4.35 5.22 4.85 5.07
Avg. Land Holdings (Hectare) 0.25 0.38 0.5 0.42
% of
Income
Earned
Monsoon Agriculture 14 28 20 25
Winter agriculture 16 4 7 8
Summer Agriculture 10 0 8 10
Total earning from Agriculture (%) 39 32 34 43
Plantations Earning from tea plantations (%) 7 0 4 6
Earning from betel leaf plantations (%) 0 0 0 3
Earning from Allied activities (%) 14 20 18 14
Earning from other Non-Farm activities (%) 40 48 44 34
[Source: Primary Survey]
27
4.4 Delivery of government assistance The previous section provided an idea about the earning distribution from different sources
and the relative importance of farm sector to rural households across different respondent
categories. This is important baseline information for assessing the enhancements of farm
income at some future point of time. But rural India has witnessed a large number of
agricultural assistance schemes and rural income enhancement schemes. The success in
delivering benefits through these schemes crucially depends on the delivery mechanism. As
is evident prom the profile of sample households, the rural households are lowly educated. To
avail the institutional benefits, they need to be made aware of the alternative schemes, their
own eligibility and the procedure to obtain the benefits.
In rural West Bengal, these farm-related benefits are almost always channelized by the Office
of the Assistant Director of Agriculture (ADA), which exists at Block Level. The ADA
Office is commonly referred to as „agriculture office‟ by the villagers and they know that for
every farm-related queries and grievances, the ADA Office is their supreme authority. The
task of liaison with the common farmers in a block formally rests with the Krishi Prayukti
Sahayaks (KPSs) in ADA office who are in the official pay roll.
In all our meeting with ADAs (involving the KPSs) we have sensed that there is a
tremendous work-load in every ADA office and there is a serious shortage of KPS personnel.
We have gathered information from the ADA offices regarding the currently vacant KPS
posts. This is described in Table-18.
Table 18: Shortage of required personnel in Block Agricultural Offices
District Block (Agro-Climatic Zone)
No. of
sanctioned
KPS post
No. of KPS
actually in service
(as of 30.11.2017)
% of vacant
KPS positions
BANKURA
Onda (Lateritic) 18 4 78
Chhatna (Lateritic & Gangetic
Alluvial) 13 5 62
Patrasayar (Gangetic Alluvial) 10 4 60
BURDWAN
Ausgram-I (Gangetic Alluvial) 16 2 88
Kalna-II (Gangetic Alluvial) 9 1 89
Salanpur (Lateritic) 6 2 67
JALPAIGURI
Rajganj (Terai Alluvial) 22 9 59
Moynaguri (Terai Alluvial) 23 6 74
Alipurduar-II (Terai Alluvial) 18 4 78
SOUTH 24
PARGANAS
Mathurapur-I (Coastal Saline) 10 1 90
Diamond Harbour-I (Coastal
Saline) 11 2 82
Patharpratima (Coastal Saline) 17 1 94
Over all sample blocks 173 41 76
[Source: responses from Block ADA Offices: Primary data]
28
It is felt from the field experience that in the absence of ready-to-consult personnel from the
ADA offices, the farmers are often in dark about their entitlements and fails to avail the
institutional assistance even if there is reasonable provision. It is felt that providing sufficient
personnel in these offices is an issue of the state administration which might not be solved in
the short run. In light of this observation, the study recommends inclusion of outside
facilitating agencies to bridge the information gap with the farmers. The recommendations
are made in the appropriate section of this report.
The much emphasised Prime Minister Fasal Bima Yojna (PMFBY) and provision of
institutional credit for agriculture at concessional rate is in force already. But it requires
farmers to have their bank accounts and Kishan Credit Cards (KCC). The study wanted to
have a baseline on the availability of KCC with the respondent households as well. But for
obtaining a KCC (issued by designated commercial bank branches, facilitated by the ADA
office), one needs to show official updated land titles to the bank. The study finds that there is
a general reluctance from banks‟ side in issuing KCC as banks‟ branch managers (who are
mostly outsiders) feel that more KCCs are potential sources of creating bad loans.
Table 19: Availability of Kishan Credit Cards (KCC) across sample households
District Block
Total
number of
survey HHs
% of HHs
obtained KCC
through Samabay
Samity
% of HHs
obtained KCC
directly from
Bank
% of HHs
without
KCC
Bankura
Chhatna 60 6.7 0.0 93.3
Onda 80 5.0 5.0 90.0
Patrasayer 60 13.3 11.7 75.0
Burdwan
Ausgram-I 84 11.9 7.1 81.0
Kalna-II 60 50.0 5.0 45.0
Salanpur 62 1.6 3.2 95.2
Jalpaiguri
Alipurduar-II 60 18.3 6.7 75.0
Maynaguri 61 9.8 18.0 72.1
Rajganj 79 3.8 24.1 72.2
South 24
Parganas
Diamond Harbour-I 60 0.0 5.0 95.0
Mathurapur-I 61 0.0 6.6 93.4
Patharpratima 82 7.3 6.1 86.6
Total 809 10.3 8.4 81.3
[Source: Primary Survey, August-October, 2017]
29
In absence of a clear land title, a farmer can also get a KCC through the mediation and
endorsement of registered Farmers‟ Co-operatives (Samabay Samiti). These Samiti‟s also
help farmers with their paper works and attracts applicants who have a clear land title as well.
The survey finds that most of the KCCs issued in West Bengal are through this Samabay
Samiti route. Table-18 describes this. The table clearly shows that in spite of great efforts
from the part of the authority, many procedural obstacles have left majority of the rural
households in West Bengal without a KCC. The main reasons identified for this failure are:
Lack of clear land titles for most of the farmers. For many farming households, the
cultivable lands had been subdivided among brothers after their father‟s death, or after
their separation from the common kitchen, without officially recording the titles.
Lack of procedural knowledge to obtain the KCC and aversion for paper works with
low education level
Reluctance of the banks to issue KCC as it is looked upon as a potential liability for
the bank branch
The renewed and simplified crop insurance scheme (PMFBY) and schemes to encourage
farmers to get their soil test done has also fared very poorly among sample households. The
crop insurance comes automatically if institutional credit is availed through KCC. But the
previous table suggest the poor state of KCC availability with the farmers. Without KCC, the
farmers are found to be unaware of how to get their crops insured. No designated official
person was found to be there to help farmers get their crops insured. Also farmers often
Krishi Samabay Samiti (KSS) in West Bengal
Krishi Samabay Samities (KSSs) are essentially Self-Help Groups (SHGs) formed by a group of farmers
which in turn combines to Primary Agricultural Co-operative Credit Societies (PACS). The West Bengal
government, in exercise of the power conferred upon it by West Bengal Co-operative Societies Act, 1983,
permitted the PACS‟ to include SHGs as members. NABARD-sponsored SHG programme acted as a
booster and the groups in the co-operative sector assumed the shape of a movement in the state. Through
periodical meetings and equal doses of regular savings, group dynamism develops amongst members over
months of existence and they become eligible for credit-linkage through the PACS. The Central Co-
operative Banks act as the facilitators and the State Co-operative Bank as the coordinator
(http://coopwb.org/self-help-group.php). The survey experiences shows KSSs play a significant role for
availing agricultural credit for its members. The credit fund of a registered KSS comes through the Central
Cooperative bank via State Cooperative Banks and these Societies are more efficient in channelizing the
credit to the eligible recipients. KSSs are important for the following reasons:
The KSSs help its members with their paper works in obtaining KCC and credit
These KSSs help the credit providing institutions in identifying the prompt payers
KSSs disburse the sanctioned credit to a group of farmers, thereby creating a multilateral guarantee
system for credit repayment
It helps its members by providing fertilizers, pesticides, tillage equipments (like harvester, zero
tillage machine, drum seeders etc) at a lower price.
Many such Samitis have own storehouse where members are provided with storage facilities of
their products at a low cost.
But the FGDs reveal few shortcomings of these Societies as well:
The multilateral guarantee process fostered by KSS sometimes acts against the prompt payers. If
the entire amount of credit is not repaid in time, then as members of the group the prompt payers
are also deprived of required credit through this channel in the next season.
Like other Registered Co-operatives, the credit availed through the mediation of KSS requires a
certain percentage of that money to be invested in Society‟s share capital. It effectively raises the
cost of credit to the farmer who needs the fund for short term agricultural use and who are not
interested in raising their financial assets (Society‟s share).
30
complained about the narrow coverage of crop insurance schemes. Only few crops can be
insured in certain seasons. Table-20 describes the ground reality of crop insurance and soil
test among the sample households.
Table 20: Ground level situation with crop insurance and soil tests
District
Bankura (Lateritic/ Gangetic Alluvial)
Burdwan (Gangetic Alluvial/ Lateritic
Jalpaiguri (Terai
Alluvial)
South 24 Parganas (Coastal Saline)
Total
Number of sample HH 200 206 200 203 809
% of sample HHs with own land 71.5 61.7 70 66 67.2
% of land-owning HHs who availed any
type of crop insurance during 2017 11.2 27.6 15.7 8.2 15.4
% of land-owning HHs who have any soil
test report ever carried out 2.8 7.1 7.9 8.2 6.4
% of land-owning HHs who submitted soil
sample but did not receive report 20.3 20.5 27.1 10.4 19.7
[Source: Primary Survey]
The last row of Table-20 is interesting. It was found that some enterprising local leaders
(often organizers of Farmers‟ Clubs) and even some local fertilizer distributors recently has
enticed rural households to get their soil test reports done. They approached the farmers and
assisted to collect the soil samples in the prescribed manner. Farmers did it under the
impression that a soil test report might be required to get loans or crop insurance in coming
days. However, they are unaware of what has happened to the report after they submitted
their soil samples. The reports didn‟t come yet and they also don‟t know who are supposed to
deliver them. It seems there is a lot of communication gap on this count. The farmers don‟t
know exactly in which way they will be benefited through a soil test report and where to get
it done. In their opinion, they themselves know their soil quality quite well. If there are expert
counselling/consultancy that are supposed to follow from the ADA office after soil test
reports, they are willing to get it done. But there is no assurance of a tangible benefit from
soil tests. On top of it, most farmers don‟t know about any laboratory facility near their
locations where soil test reports are prepared. This study recommends setting up of
specialized soil testing laboratories adjacent to ADA offices in each block either purely by
engaging private agencies through financial incentives, or through PPP models. Soil tests
reports should be provided in a time-bound way and it should be accompanied by expert
opinion on the optimum cropping pattern for that soil. From the findings from field survey,
the study also recommends wider coverage of PMFBY incorporating more crops and
vegetables covering different seasons.
4.5 The rural credit market and credit availability
31
One crucial input for enhancement and intensification of farm activities, may be right after
irrigation facility, is agricultural credit. A policy oriented study on possibility of doubling
farmers income needs to be detailed on this issue. In this study, detailed information on the
respondents‟ current indebtedness, their purpose for obtaining credit, credit sources and
repayment periods was collected and analysed. Rural households often take credit for
unproductive reasons and emergencies like consumption, social occasions, health issues and
non-farm business ventures. Looking at the stated purposes of taking credit, the study
identified the credit profiles which were taken purely for enhancement and diversification of
activities relating to agriculture, pisciculture and animal husbandry. The nature of such credit
provides an idea about the credit need in the rural sector of West Bengal for farming and
allied activities. These are summarized in this section.
Table 21: Distribution of sources of current credit for farming and allied activities
Credit Sources
Total number of current credit availed by respondent HHs across zones
Bankura (Lateritic/ Gangetic Alluvial)
Burdwan (Gangetic Alluvial/ Lateritic
Jalpaiguri (Terai
Alluvial)
South 24 Parganas
(Coastal Saline) Total
Through SHGs 8 2 9 1 20
Directly from Gramin Banks 0 0 4 1 5
Directly from other commercial Banks without KCC
4 6 32 7 49
From commercial banks through KCC 15 11 21 4 51
Through Krishi Samabay Samity 21 39 10 4 74
BSKP12 1 0 0 0 1
Neighbour / Relative 1 2 4 2 9
Private money lenders 8 15 14 5 42
Others 3 6 7 5 21
Total 62 81 101 29 272
[Source: Primary Survey]
Table-21 shows that there are 272 instances of current credit availed by the respondent
households that were taken solely for farming and allied activities. It also shows that the
majority of them are presently institutional. But it is also notable that private money lenders
are still significantly present in rural West Bengal. The Coastal saline zone (district of South
24 Parganas) turned out to be a poor performer in credit market while Terai alluvial zone
(Jalpaiguri district) is the most active. This is in conformity with the relative dynamism in
farm sector in these districts. Previous sections have shown that Terai Alluvial is the most
active zone in agriculture followed by Gangetic Alluvial. The proportion of current credit
instances are spread over the zones in similar line. It reaffirms the claim that these responses
are indeed related to credits availed for farming and allied activities. The coastal saline zone
stands out as the zone with the least penetration of institutional credit. As much as 40 percent
of the total number of credit in this zone had originated from non-institutional sources.
12 Bangla Swanirbhar Karmasansthan Prakalpa (BSKP) is a special vehicle launched by the Government of
West Bengal to generate self-employment in the urban & rural areas through promotion of tiny scale units of
production, manufacturing, trade or services.
32
Table-22 provides the break-up of these credits across different usage. It is seen that over 90
percent of these credits are indeed related to farming. Animal husbandry scores over
pisciculture for credit requirement.
Table 22: Distribution of number of credits availed across usage
Credit Sources
Total number of current credits availed by respondent HHs across
farming and allied usage
Agriculture Pisciculture Animal
husbandry TOTAL
Through SHG 13 1 6 20
Gramin Bank 4 0 1 5
Commercial Bank (without KCC) 43 1 5 49
Commercial Bank (under KCC) 49 1 1 51
Through Krishi Samabay Samiti 74 0 0 74
BSKP 0 0 1 1
Neighbour/ Relative 7 1 1 9
Private money lenders 38 3 1 42
Others 20 0 1 21
Total 249 7 17 272
[Source: Primary Survey]
To understand the credit needs further, we analysed the average sizes of current credits, their
repayment periods and the effective average annual interest rate that the debtors are paying
for them. Such information reveals the nature and problems in rural credit market. From
Table-23, it is observed that regional rural banks (Gramin Bank) are disbursing credit for a
much longer period and of a larger average size. Such credits, though availed by very few
households, carry the lowest average rate of interest. Credits from SHGs carry an effectively
high rate of interest for the borrowers, smaller in size and have a smaller repayment period. It
was found that credits provided by private money lenders bear a very high rate of interest and
also have the lowest repayment period. It is understood that such credit, if failed to get repaid
within stipulated short time, attracts an even higher interest.
One interesting point might be noted relating to the effective interest rate for credits availed
through KCC or KSS. As per official guideline, the rate of interest is linked to the base rate
and left to the discretion of banks. Generally it is 7 percent with a 4% subvention provision
by central government for prompt payers. From the primary survey it was found that previous
defaulters often ended up paying a higher rate of interest (7+4= 11 percent) if their repayment
of principal does not take place within stipulated period. The study finding of more than 7
percent effective rate of interest thus indicates the presence of some defaulters among the
respondents.
33
Table 23: Credit sizes, duration and interest across sources
Credit Source
Average credit
size (Rs.)
Average credit
duration (months)
Average Annual
Interest rate
payable
Through SHG 21,825 12 19.9
Gramin Bank 85,200 30 7.0
Commercial Bank (without KCC) 58,384 21 10.2
Commercial Bank (under KCC) 51,461 13 7.4
Through Krishi Samabay Samiti 33,021 13 7.7
Neighbour / Relative 38,222 Unspecified 45.0
Private money lenders 40,588 10 46.7
Others 16,321 12 10.9
[Source: Primary Survey]
Table-24 further breaks up the credit sizes according to their usage across different credit
sources. Though the averages shown against pisciculture and animal husbandry had been
calculated on the basis of very few observations and hence might not be statistically reliable,
it can be sensed that pisciculture and animal husbandry requires credits of larger sizes.
Table 24: Average credit size for different usage
Credit Sources Agriculture Pisciculture Animal
Husbandry
SHG 27,731 10,000 11,000
Gramin Bank 69,000 No observation 1,50,000
Commercial Bank 53,186 70,000 1,00,760
Krishi Samabay Samity 33,021 No observation No observation
K.C.C 51,827 50,000 35,000
BSKP No observation No observation 1,30,000
Neighbour/ Relative 19,143 2,00,000 10,000
Private money lenders 33,413 1,40,000 15,000
Others 16,638 No observation 10,000
Average 38,217 94,000 57,720
[Source: Primary Survey]
34
Agricultural credit through KCC route is the most desirable way of financing farmers‟
requirement. We have already seen (Table-22) that most of the credits through KCC are
facilitated by the Krishi Samabay Samitis. There are some hidden costs which the debtor
might need to bear for availing such credits. We wanted a look at the differences, if any, of
KCC loans availed through these alternative channels. Table-25 describes this. Table 25: Nature of credit against KCC availed through alternative channels
Source
Number of
HHs having
KCC
Number of
HHs having
loan from
KCC
Average
Loan
duration
(in month)
Average
Annual Rate
of Interest
(%)
Average
Loan Size
(Rs.)
Credit against KCC
facilitated by Krishi
Samabay Samity 83 74 13 7.6 33,493
Credit against KCC
directly from commercial
banks 68 49 13 7.3 50,856
[Source: Primary Survey]
It is seen that proportionately more number of households availed credit through KCC if it is
mediated by the Samabay Samitis. It implies that these Samitis might be following up with
procedural help to arrange credits for its members. Though the rate of interest incurred is
marginally higher and the loan size is less, compared to the cases where loans are directly
availed from commercial banks. The finding that proportionately less number of KCC
holders could avail credit (without the mediation of Samabay Samitis) is in conformity with
the field experience that local managers of commercial banks are reluctant to grant credit on
KCC account.
4.6. Impact of irrigation and credit on farm income
For enhancing farm income, it is a common knowledge that irrigation should be improved
and institutional credit should be made available to the farmers. Since the aim of this study is
to find out how „doubling of farmers‟ income‟ is possible within limited time, we wanted to
check the incremental effect of household income from these two crucial farm inputs.
Due to the carefully dispersed sampling strategy, the study was able to include enough
sample households with varied irrigation facilities for each agro-climatic zone. As we have
also collected detailed credit profile of the respondents, we were able to separate out the
sample household in each zone in the following three categories:
Landowning households with no irrigation facility and no agricultural credit availed
during 2017
Landowning households with some type of irrigation sources in winter and/or
summer, but no agricultural credit availed during 2017
Landowning households with some type of irrigation sources in winter and/or summer
and also some agricultural credit availed during 2017
35
The study wanted to look at the differences in average annual income of these three
categories of households across the agro-climatic zones. Since the categories are made on the
basis of irrigation and agricultural credit, the inputs are obviously related to the agricultural
landholding of the households. For meaningful comparability, the household earnings had
been normalized with respect to landholding by converting the farm incomes into a common
„per hectare earning from agricultural land‟.
Figure 3: Effect of irrigation and credit on households' annual income
The figure above establishes very convincingly the effect of these two crucial inputs on
agricultural income. The agro-climatic zone wise distribution also helps us to understand the
relative importance of these two inputs for a representative household with „one hectare of
farmland‟. The figure shows that for Terai Alluvial zone, both credit and irrigation has high
potential to enhance farm income. In Gangetic alluvial zone, the potential for such increase is
more through credit provision but less through irrigation. In Coastal saline zone, irrigation is
a greater need than credit to enhance farm earning. The corresponding numbers are provided
in Table-26.
Table 26: Estimated ‘income effect’ of irrigation and credit provision
Agro-climatic
zones
Average annual agricultural income (calculated as Rs/per hectare)
Estimated annual HH income
from agriculture per hectare
without any irrigation and
credit provision
Estimated %
increase in
income through
irrigation alone
Estimated %
increase in income
through irrigation
and credit provision
Gangetic Alluvial 44,528 12 65
Terrai Alluvial 50,894 69 189
Lateritic 25,282 70 128
Coastal Saline 44,960 47 57
[Source: Primary Survey]
0
20000
40000
60000
80000
100000
120000
140000
160000
Gangetic Alluvial Terrai Alluvial Lateritic Coastal SalineAnnual
Inco
me
per
hec
tare
(R
s.)
Agro-Climatic Zones
No irrigation and no credit availed
With irrigation but no credit availed
With irrigation and with some credit availed
36
The above analyses indicate that through proper delivery mechanism of agricultural credits in
required quantity, coupled with appropriate irrigation facilities, „doubling of agricultural
income‟ is technically possible within a short time period. However, putting in place the
required infrastructure and making institutional changes are the main challenges that need to
be addressed by the policy authority.
4.7 Households’ awareness, problems and diversification plans
In the Focus Group Discussions in various places throughout this survey, and in conducting
the household surveys, it transpired that there is a communication gap regarding various
farmers‟ assistance schemes throughout all agro-climatic zones. It seems that there is no
dearth of assistance programmes for rural agricultural households to support their farming
activities. But the rules and regulations, the appropriate authority to approach, the eligibility
criteria and the exact nature of assistance that the beneficiaries are eligible to get remained
largely unclear to the sample respondents. They often don‟t know under which scheme they
are eligible to get benefits, though they sometimes makes applications facilitated by some
neighbours or local leaders who come up with their own personal reasons.
During the survey, each respondent was asked about their awareness regarding some major
assistance programmes relating to agriculture. The respondents‟ awareness level had been
judged by the interviewer and one is marked as „aware‟ against a specific programme/
scheme if he/she was able to tell the eligibility criteria and the nature of benefits correctly.
The following table shows that, except for Kishan Credit Card, the awareness level for other
major centrally sponsored assistance schemes is abysmally low among the respondents.
Table 27: Sources of awareness for major Assistance Programmes
Sources of information Kishan
Credit Card
Pradhan
Mantri Fasal
Bima Yojna
Paramparagat
Krishi Vikas
Yojna
Pradhan
Mantri Krishi
Sinchai Yojna
Village Panchayet Office 80 4 2 1
Office of the ADA 36 0 2 0
Local Political leader 20 0 0 0
Neighbours/ relatives 66 4 2 0
Electronic Media 3 0 0 1
Print Media 3 1 0 0
Total number of respondents who are
reasonably aware 208 9 6 2
[Source: Primary Survey]
It comes out that the village Panchayet is a better source for awareness building. Other than
that, awareness is generally propagated through fellow villagers and relatives. The financial
provisions for making awareness camps regarding various agricultural assistance
programmes might be shifted to the Panchayet offices rather than burdening the office of the
ADA with this responsibility. Advertisement in print or electronic media seems to have not
worked for the programmes listed above.
37
In continuation of the discussions with the respondents, the study elicited the remarks from
the households regarding major problems that they consider as bottleneck to enhance their
farm income. They were asked to mention two to three such problems according to their
priority ranking. Some of the responses were vague and discarded. The rest is summarized in
the following Table-28. The sum of responses adds up to more than the sample size because
more than one response was considered. The usefulness of the table is that it reveals the
overall priority ranking of major problems as revealed by the respondents.
Table 28: Major bottlenecks in enhancing farm income as envisaged by the respondents
Problem statements No. of HHs agreed out
of 809 HHs
% of HHs identifying the
problem as very
important
Lack of procedural knowledge to access
government support schemes 591 73.1
Lack of access to KCC and government officials 385 47.6
Lack of knowledge in bank loan procedure and
bank‟s reluctance to help 135 16.7
Lack of assistance in getting soil test report
done 112 13.8
Lack of mortgageable assets for availing credit 54 6.7
Lack of nearby wholesale market 40 4.9
Lack of good transport facility 22 2.7
Lack of local availability of raw materials 9 1.1
[Source: Primary Survey]
The table brings out the fact that there is a serious problem of delivery of various farmers‟
assistance schemes floated by both central and state government. The work burden of the
office of the ADA and absence of sufficient number of KPSs has been identified and
discussed earlier. The procedural hazards in availing agricultural credit through banks have
also come out in earlier discussions. Table- 28 confirms our earlier analysis.
The respondents were also asked about their most important requirement for increasing farm
income. Again some of the responses were vague and discarded. The rest is summarized in
Table-29. It comes out that most of them are in need for some help in irrigation front. Either
they are asking for government to provide better infrastructure for surface water storage or
management (building check dams, excavating ponds, extending irrigation canal etc.), or they
want government to set up facilities for cheaper access to ground water (government
provision of shallow/submersible pump sets). A significant number of them are also looking
for better procurement and support price for their farm products.
38
Table 29: Households' expectation regarding government support
Households‟ needs for enhancing farm income
No. of HHs
mentioning the
requirement
( out of 809 HHs)
% of HHs
identifying the
requirement as most
important
Development of new irrigation infrastructure
(check dam/ pond/ canal extension) 233 28.8
Govt. help in availing irrigation equipment
(shallow/ submersible) 205 25.3
Better support price and easier procurement of farm
produce 137 16.9
Various types of training (farming and allied) 74 9.1
Timely seed distribution by government 33 4.1
Special credit schemes for livestock and fisheries 11 1.4
Greater coverage for Crop Insurance schemes 10 1.2
Special marketing assistance for organic products 4 0.5
[Source: Primary Survey]
Finally, respondents were also asked about any additional earning plan they are
contemplating with, which is apart from their existing farm practices. They were also asked
about the credit requirement and expected repayment period to execute such plans. The
responses were divided into some broad categories. This is reported in Table-30.
Table 30: Households' plans for diversification and corresponding credit requirement
Types of individual income-
enhancing plans
Number of responses
(out of total 809)
Average credit
requirement (Rs.)
Average Required
duration of credit
(months)
Leased in Agriculture 6 80,833 18
Winter Agriculture 2 50,000 18
Summer Agriculture 3 21,667 16
New plantation (mostly tea) 12 88,333 30
Pisciculture 20 1,28,500 30
Animal Husbandry 45 1,70,667 33
Agro Business 33 1,75,091 30
Tailoring & Handicraft related
business 6 1,11,667 28
Other Non Agro Business 44 1,72,955 34
Total 171
[Source: Primary Survey]
39
It is observed that only around 20 percent of survey households answered this question in a
concrete way. The diversification plans cover agricultural ventures as well. Some of the
respondents who are deprived of irrigation water for monsoon and summer cultivation
wanted to begin that activity. Some landless farm labourers wanted to lease-in land and
wanted to carry out their own agriculture. Some respondents wanted to diversify into fishing
and animal husbandry in a more commercial way. And of course some of them wanted to get
into non-farm business activities.
It is interesting to note that a significant number of them want to diversify into fisheries and
animal husbandry. The table reveals that there is ample scope to pump in new credit through
schemes specialized for these activities. Table-30 also shows that these credits need to have a
larger size than usual agricultural credit and a longer repayment period.
5. Discussions on study findings The tables and figures presented in the previous section indicate that through proper
mechanism of delivery of agricultural credits in required quantity, coupled with appropriate
irrigation facilities, „doubling of agricultural income‟ is technically possible within a short
time period. However, putting in place the required infrastructure and making institutional
changes are the main challenges that need to be undertaken by the policy authority.
In this regard, this study comes up with a set of policy suggestions that are spelt out in the
next section. This section provides some additional points to justify those suggestions. The
points discussed in this section are results of:
Detailed Focus Group Discussions with the Assistant Directors of Agriculture
(ADAs) of all the twelve sample Blocks and the Krishi Prayukti Sahayaks (KPSs) of
his/her office
Observations from field by the Principal Investigator and the surveyors (research
students).
Discussions with village Key Informants (Progressive Farmers‟ as identified by ADA
office), office bearers of Farmers‟ Clubs, and locally influential and/or renowned
persons with whom the enumerators talked at length during the field survey.
Comments and opinions provided by the respondent sample households outside the
set questions in the questionnaire.
Lastly and most importantly, the information collected through different modules of
the structured questionnaire
The major problems in the state that can be identified from the field level discussions and
collected information can be categorized broadly as –
Problems with the official delivery system of Assistance Schemes
Problems with irrigation
Problems with rural credit
40
5.1 Problems with the delivery system of farmers’ assistance schemes
As discussed earlier, the block ADA offices were found to be operating under manpower
shortages. It is resulting in difficulty for the officials in reaching out to the farmers with
various assistance schemes being sponsored by the central and state government. All the
ADAs in the sample Blocks turned out to be very sincere and motivated to their work. But an
ADA personally cannot reach out to all farmers. The KPS is supposed to be the single liaison
point between the government and the farmer. As shown previously (Table-18), the state is
facing a shortage of KPS in all blocks. As a result, the ADAs could do nothing but rely on
some individuals from various villages in his block and farmers‟ associations (if any) to
execute their duties.
For example, if some training camps are to be arranged, or some agricultural inputs (like
seeds) are to be distributed within a targeted timeline, the ADA office calls on some village
individuals to arrange that. These individuals generally happen to be more dynamic,
educated, clever and enterprising landholders in the block. It is no surprise that they often
hold some political clout in their villages which is strengthened by their proximity and access
to the ADA office. As a result, the final distribution of government assistance might not be
reaching to the people who need them most.
The study found all the ADAs in 12 sample Blocks very sincere and they often tried to reach
out to maximum number of farmers by asking them to organize themselves in Farmers‟ Clubs
(FCs). Such FCs are then used as a vehicle for the respective ADAs who often patronize them
by channelizing funds for various agricultural training programmes and other government
assistance to farmers. But the study finds that such FCs are usually very large in size and is
effectively controlled by a handful of persons. Most of the other members are naive enough
and has no say in the day to day functioning of the club. Successful distribution of various
government assistance among the club members need active and homogenous membership
profile – which such clubs lack in most cases.
The KPSs were also found to be shouldering large workload as many such posts are lying
vacant in ADA office. The sample respondents in most cases informed that there was no visit
by government officers or KPSs in their village for quite some time. So, the study finds that
the lack of office personnel in the ADA office at Block level is giving rise to unequal
distribution of government assistance which is mostly being cornered by a handful of
educated and dynamic farmers in villages.
This situation was found to be comparable across all agro-climatic zones in West Bengal. It is
an administrative problem rather than a local resource related problem. So, a policy
recommendation on this point has to be state specific and not zone specific.
5.2 Problems with irrigation infrastructure
Among the agro-climatic zones, the intensity of the problem of irrigation is unequal. While
Lateritic and Coastal Saline zones have a more severe deficiency in irrigation water, the Terai
Alluvial zone is most fortunate in water availability for the numerous small and medium
water channels flowing across it in the Himalayan foothills. But then also, there are pockets
of irrigation deficit areas and blocks. If we look at the block level and village level data, the
problem of irrigation is reported to be a problem in parts of every block, if not in every
village, across all agro-climatic zones.
41
Providing irrigation facility to farmers obviously stands out to be a meaningful policy handle
to enhance farm income. As shown in the study findings previously, presence of irrigation
alone can largely increase the return from agricultural land, especially in Terai Alluvial and
Lateritic zones (Table-26). This is also supported by the cropping intensity indices of
irrigated and non-irrigated farmlands (Table-13).
That the farmers themselves expressed the need to have better irrigation for their betterment
is amply demonstrated by Table-29. In connection to credit need, their overwhelming
response was to get technical (knowledge) help from the government to avail credit. But in
connection to irrigation, their response was to ask for government initiative to provide them
with more irrigation water.
Many of the respondents wanted the government to set up shallow/submersible units to lift
groundwater for their crops. While this can improve the cropping intensity in the short run, it
would have negative ecological implication for sustaining the local water table in the long run
due to large scale ground water lifting.
A positive aspect of this survey is that the farmers are aware of this ecological peril of ground
water lifting. Table-29 shows that more number of respondents want the government
intervention in irrigation in the form of check dams/pond/canal extension, compared to those
who wanted the service of shallow/submersible. There are already incentive schemes
launched by the state government for rain-water harvesting. The MNREGA work is also
creating and excavating irrigation ponds. Larger fund allocation for these schemes is
warranted for farm-income enhancement. These schemes are more in need for Coastal saline
and Lateritic zones.
The study found one good example in this respect in the Lateritic zone of Bankura district
where a couple of IWMP projects were supported by NABARD. At least one of these
projects had helped in income generation of a large number of villagers with an able local
leadership. Such models of integrated watershed development need to be scaled up.
5.3 Problems with rural credit
The other problem that emerged prominently across all agro-climatic zones is the lack of
availability of institutional credit in required quantity and for required duration. In spite of
lots of inroads made by various government agencies over years, the rural financial market
still now have a significant presence of local money-lenders (mahajans) and other non-
institutional credit sources as is described in Table-21. This happens in spite of the
significantly higher interest rate charged by them.
The most significant vehicle to increase farmers‟ income is obviously to supply them with
their required amount of credit. This is amply demonstrated in Table-26, which shows that
availability of credit can increase the farm income significantly across all agro-climatic
zones. The foremost reason for farmers not being able to access institutional credit is because
of the problem of mortgages. Theoretically, farmers can get loans through Kishan Credit
Cards without mortgages. But Table-19 also shows that only a small number of farmers
actually possess KCC and only a subset of them could avail credit through it. The reason for
not having KCC largely coincides with farmers being unable to access institutional loans. For
42
most of the farmers, there is dispute over their title of the land that they cultivate. This might
partly be a specific problem in West Bengal with its land reform measures in the past. But
also fragmentation of landholding through generations has been carried out on mutual
understanding among the family members in rural Bengal without the corresponding official
documentation. KCC can be obtained without landholding through the mediation of farmers‟
co-operatives (Samabay Samiti). But the respondents often pointed out that they felt banks
are unwilling to provide any help for seekers of credit who have got the KCC through
Samabay Samiti.
Table-23 shows that average credit size availed from SHGs, compared to that from the
commercial Banks, is significantly less. The credit that can be obtained from SHGs and can
be put into agricultural use is often too small compared to the requirement. Such SHG loans
cannot fulfil the credit requirement of rural sector to enhance farmers‟ income up to their
potential. SHG loan can have marginal impact on the HH earning, that too through the
womenfolk of the households.
One recurrent note from discussions was that the farmers‟ need credit for longer duration. A
6-12 month credit repayment obligation often pushes the farmers to distress selling. For
example, many of the potato farmers responded that they could have obtained good prices if
they could afford to keep their harvest in store for some time. They were forced to sell at
meagre price immediately after harvesting as they had to repay the loan in time. These field
level experiences converge to the fact that the system of providing rural credit needs some
administrative changes.
One successful and innovative example has been found (mostly prevalent in the North
Bengal) by the system put up by one recently incorporated commercial bank (Bandhan bank).
Its system might not look very ethical but this survey had found that it is working very
efficiently. The main reason for this bank‟s rural success story is that it is providing credit
without any mortgage. This is a huge attraction for the rural folk as the mortgaging is a huge
issue for them. The Bandhan Bank scheme is actually appropriating a high interest from the
debtors who are still flocking to the bank because of its procedural simplicity.
The bank is reaching out to the farmers by engaging local village persons as commission-
agents who get all the formalities done on the farmers‟ part at their doorstep. The mortgage
issue is bypassed relying on these agents‟ prudence and local leverage. An agent would not
arrange credit facility for a villager who has larger chance of defaulting because that will
jeopardize his own flow of commission-income. Also, he will use his personal influence to
see that his clients are paying back their dues to bank on time. On the farmers‟ part, the
timely repayment to the bank is a priority as he can obtain, in his next credit application,
larger amount more easily and quickly depending on his own repayment record. The bank is
recovering this additional cost of reaching out and risk of non-insured loans by charging an
interest rate quite cleverly that is much higher than commercial bank‟s usual lending rate.
Going by the field information, these agents of Bandhan Bank is apparently asking for an
annual interest rate of 12 percent on unsecured loans repayable in 12 months. The interest is
being calculated to the full loan amount and for one year. The total repayable (at the end of
the year) amount, thus calculated, is then divided into 52 Equal Weekly Instalments (EWI)
and the debtor has to start paying these EWIs from the very next week after availing the loan.
So, the interest is being paid on the whole of the principal amount while the principal is
43
reducing weekly. The real rate of interest charged by this scheme, therefore, is much higher
than 12 percent.
However, this scheme, due to easy access, lack of procedural hassles and low one-time
repayments instalments (52 EWIs) is found to be very attractive to the farmers. Taking cue
from this operation, new small scale microfinance companies have cropped up in North
Bengal, with anonymous sponsors and without their known office addresses. They are
providing funds to the farmers under similar schemes through local agents. For the farmers, it
turned out to be a better option compared to private money lenders who charge explicit and
high rate of interest and formal institutions (other commercial banks) which tend to deny loan
applications without mortgages.
5.4 The role of ‘progressive farmers’ and demonstration effect As already indicated by previous discussions, there is a significant deficiency in awareness
building among the rural households regarding their entitlements for various assistance
programmes offered by central and state governments. A natural corollary would be to find
ways to reduce this information gap and helping the lowly literate farmers so that they can tap
these provisions and increase their earning flow. However, this type of policy suggestion
ignores one crucial aspect of farming and rural livelihood – that is the role of
„entrepreneurship‟ in rural households. It is one big aspect that often makes a lot of difference
in a household‟s economic status. Every rural household, which is not enjoying a permanent
salaried employment, makes some sort of choice in the „risk-return‟ space in deciding its
livelihood path. It is the lack of clear idea of „returns‟ against various types of risks in
agriculture or other non-farm activities that holds back rural households in venturing into new
activities, even if they are aware about various assistance programmes.
It was found from the field survey at different locations that the „demonstration effect‟ of
successful entrepreneurship in the neighbourhood, with or without availing government
assistance, usually makes a large impact in the psyche of neighbouring households regarding
what they want to do to enhance their income. Advices and counselling by government
officials and/or other agencies on the ideal cropping pattern, fertiliser use or introduction of
new technology might go in vein unless there are some practical field demonstration of
enhanced benefit which is actually shown to be reaped by some fellow villager. Here comes
the role of entrepreneurship, which is usually demonstrated by some „first movers‟ among the
villagers who are generally identified as „progressive farmers‟. It cannot be predicted
beforehand who will make the move. But once one or more such persons emerge from within
a village, they usually catch the attention of the concerned local officials (ADAs/KPSs).
These progressive farmers generally get the benefit of more information flow about the
assistance programmes and new technology that might be suitable for them. The awareness of
such programmes is then transmitted to the other fellow villagers, who are already convinced
about the programmes‟ potential by such demonstration. The field experiences suggest that
existence of few such progressive farmers in a village usually sets positivity and dynamism
among the neighbouring other households regarding better choice of livelihood using
different government assistance programmes.
In many cases, new technology and a successful break from the traditional cropping pattern
has been the result of „demonstration projects‟ initiated by dedicated agencies like the Krishi
Vigyan Kendras (KVKs) and/or NGOs, and has been carried out on own plots by such
progressive farmers. The study found that building a larger pool of progressive farmers is an
44
effective way of propagating new technology and cropping pattern among rural households
and spreading awareness about various income enhancement possibilities. The study also
found that KVKs are crucial district level institutions that bring out hidden entrepreneurs in
farming activities with their comprehensive package of inputs and consultancy. The study, in
one of its major recommendations, calls for further spreading out of KVK demonstration
projects at Block level. In every agro-climatic zone, there are such progressive farmers who
could be identified by the concerned KPS/ADAs. The following specific cases, one each
from the four agro-climatic zones, are examples of progressive farmers who could effectively
utilize various options and assistances to enhance their own income considerably and creating
dynamism among the fellow villagers.
(i) Zone: Gangetic Alluvial
Mr. Mantaj Ali Seikh of Dafarpur village under the Kalna-II block of Burdwan district was
identified as a prominent case of successful entrepreneurship in farm sector by the local
agricultural officials. A detailed interview with him revealed the following points.
Mr. Ali had recently switched to cultivation of a high-value rice variety (locally called
Gobindabhog) instead of cultivating the otherwise common variety (Swarna). He
made use of the assistance provided under PKVY project and carried out his farming
organically. .
Mr. Ali diversified into horticulture on a significant scale. Although Kalna-II block is
a belt for paddy and jute, he has started cultivating many fruits like Mango, Jackfruit,
Papaya, Guava, Dragon fruit etc. Such diversification proved to be commercially very
successful and added to his income significantly for last two years.
This success had attracted fellow villagers and Mr. Ali went on to set up a Farmers‟
Club few years ago under the accreditation of NABARD, which has been
continuously encouraging the farmers for income enhancement through promoting
agriculture, horticulture and allied activities. This club helped its members in
obtaining KCC and has been organizing various agricultural training programmes
with the help of local ADA office throughout the year.
Recently, by the members‟ expressed interest in horticulture following the successful
demonstration by Mr. Ali, NABARD has sanctioned a Green House project to this
club to produce vegetables like onion, cauliflower, coriander leaf in off season.
Mr. Ali also got Krishak Ratna award in 2013 and Krishi Ratna award in 2015 by the
government of West Bengal.
(ii) Zone: Lateritic
Mr. Bikash Dhak of Dalpur village under the Chhatna block of Bankura district was
identified as a progressive farmer through survey experiences and was also by the local ADA.
45
Mr. Dhak almost alone has changed the cropping pattern of his village through
demonstration of successful entrepreneurship. He made the village a strong belt of
vegetable production.
Geographically Chhatna is a remote block of Bankura district nearer to the Susunia
Hills and falls under the Lateritic zone, where lack of irrigation and irregular rainfall
put severe constraints to cultivation throughout the year.
Till few years ago Dalpur was a village with only monsoon cultivation of paddy. But
Mr. Dhak was the first one to step out in that area who did experiment with onion
cultivation in monsoon season in 2014 under a demonstration package initiated by an
agricultural university. He got huge success.
After that success story, many other local farmers replicated his model of monsoon
onion cultivation and could increase their income significantly.
Mr. Dhak is also a pioneer of organic farming by using different bio fertilizers and
training to the farmers of that region.
He has developed a regular marketing connection with „Sufal Bangla‟ . It is a venture
by the agricultural marketing department of the government of West Bengal that
establish a direct interface between producer and consumer bypassing all the
intermediaries.
(iii) Zone: Coastal Saline
Mr. Tapas Sardar of Daudpur Village of Mathurapur-II block, under the district of South-
24 Parganas, was identified as a progressive farmer by the local ADA. A detailed interview
with him revealed that
Mr. Sardar is a leading person of that village who has been encouraging the villagers
about the possibility of income enhancement through agricultural-allied activities.
Mr. Sardar had adapted the “Sundarini Project” initiated by the government of West
Bengal for development of dairy sector. He encourages local households in milk
production which he helps to be procured by the government-run dairy farm providing
remunerative price for milk. This adds to significant cash income of the local
households and is fast increasing their interest to expand the animal husbandry sector
there.
Also, he took a great initiative by helping local women in setting up an SHG which is
successfully making commercially viable handicrafts from the dried stems of a locally
available water plant „Sola‟ (Aeschynomene aspera).
He had also adopted organic farming under the PKVY scheme and helped to spread it
among fellow villagers
Mr. Sardar had been playing very crucial role for implementing various technical
interventions prescribed by KVK of South 24 Parganas (at Nimpith).
46
(iv) Zone: Terai Alluvial
Mr. Surendra Biswas of Yashodanga village of Alipurduar-II Block was identified as a
progressive farmer through survey experiences.
Mr. Biswas is an enlisted farmer under PKVY scheme and has been organically
farming various local (folk) rice varieties like Dudheswar, Gobindabhog, Kalabhat,
Keralasundari etc. for last three years.
He is also attached to various agricultural activities of Terai Reasearch Centre and
North Bengal Agricultural University from where he has got consultancy and seed
support for various folk rice varieties.
Last year he had got assistance for vermin-culture from PKVY scheme which helped
him to increase the yield of his rice output significantly.
He is also a leading farmer of marigold cultivation in that region.
Apart from that he has a flower nursery which is providing him approximately Rs.
1,50,000 as annual net return. He has also got Krishak Ratna award for his
spontaneous effort to adopt alternative agricultural practices.
His success provided a positive demonstration effect and other households in the
village are gradually shifting to his model of crop-mix and organic farming using
various assistance programmes like PKVY.
5.5 Scenario building at farm level
This study also attempts to come up with empirical estimates of effects of certain types of
interventions on household income on the basis of survey data. The effects are supposed to
vary across agro-climatic zones, and hence are separately estimated for each zone.
It is important to note that this attempt to build a „scenario of enhanced income‟ has been
done on the basis of a cross-section data obtained through a one-shot survey. Naturally, it was
carried out through a comparative approach across subgroups of survey sample with respect
to differentiated interventions. It is not based on „observed dynamics‟ of household income
through various interventions that could have been possible only through a time series data.
Also, household level specificities and endowments influence income dynamics of different
households differently. Some of these household level factors could have been identified
through a „panel dataset‟, where same set of households are observed through several time
points. This was also not possible with the present study. So, the attempt has been made to
find out the income or earning effect of an „average household‟ under different types of
interventions. For meaningful policy prescription to agencies like NABARD, the
interventions were confined to two broad types - credit availability and provision of
irrigation. Other factors that also have influence on rural household income (proximity to
urban centres, good road connectivity and electricity) were kept out of analysis as the policy
prescriptions on those interventions might be very generic and not feasible in the short run.
47
These two types of interventions can be made by agencies like NABARD through its grass
root level operations. Many assistance programmes of NABARD are directed towards
creating micro-irrigation facilities through projects like IWMP. While there are costs incurred
on this account, the estimates of financial returns are unknown, since such interventions are
of the nature of social investments. Success of credit deployments, on the other hand, might
be measured in terms of timely repayments by the borrowers. But there also, the optimum
credit size required for a targeted increase in income is difficult to estimate. This is more so,
as the deployment of credit takes different ways depending on the preferences, skills and
supplementary endowments of the borrower. With a cross-section data, what can be
scientifically estimated is the „average effect of credit on income‟ by splitting the sample into
subgroups with respect to their credit intake.
In this section, attempt has been made to estimate the effect of irrigation and credit on farm
income and effect of credit on non-farm business activities and livestock earning. In each of
the cases, the methodology is to split the sample into subgroups depending on certain criteria
and then observing the difference in their averages.
To estimate the effect of credit and irrigation on farm income, a subset of sample households
were considered that has agricultural landholding of more than 0.5 hectare. This was done
after in depth analysis and cross tabulation with the data which revealed that the households
with very small landholding are showing maximum variation in their „per hectare annual
farm income‟. This is plausible since for small holders, difference in their annual income
caused by differences in their human capital and proximity to markets and/or other specific
household level factors, get multiplied many fold when normalized by a large multiplicative
factor to obtain „per hectare income‟. It blurs the effect of interventions on farm income. The
bigger landholding households are more homogeneous in terms of their farm income and
provide a more dependable basis for inter-group comparisons.
To determine the effect of irrigation and credit on farm income, firstly landholding
households (more than 0.5 hectare) in each agro climatic zone were identified. Then the three
top performers in terms of „annual farm income from one hectare land‟ were separated out
from each zone – as they are considered leaders or models defining the frontier of farm
income that can be achieved with the available technology within that zone. The rest of the
households were divided into two parts – „have‟s and „have-not‟s – in terms of irrigation and
credit.
In this way, the „effect‟ of irrigation on annual farm income from one hectare of land has
been estimated for each agro-climatic zone, which is shown in Table-31. It is to be noted that
the income figures estimated in the table would not exactly match to the figures reported
previously in Table-15 (annual average household income from all sources across agro-
climatic zones). In some cases, the annual farm income reported in Table-31 is more than
annual income from all sources (Table-15) reported for the same zone. This is because the
former table included all households in that zone including the landless, while Table-31
involves only the households with considerable agricultural landholding.
48
Table 31: Effect of irrigation and potential farm income from one hectare farm land
Agro-Climatic
Zones
Average Household Income from Farming activities from 1 Ha land
Households
without any
irrigation for
agriculture
(Rs.)
Households
with irrigation
sources for
agriculture
(Rs.)
% increase in
annual income
accounted by
irrigation
Potential
Income frontier
(average of
three leaders
with credit &
irrigation)
(Rs.)
Gangetic Alluvial 38,418 50,389 31 2,11,007
Terai Alluvial 44,617 86,610 94 3,85,128
Lateritic 22,646 48,300 113 75,046
Coastal Saline 62,916 77,491 23 1,22,501
[Source: Primary Survey]
The above table shows that there is significant scope for increase in farm income through
developing sustainable micro-irrigation projects (preferably rain-water harvesting) in
Lateritic zone and even in Terai-Alluvial zone. However, this scope is limited in Gangetic-
alluvial and Coastal saline zones. The Table also provides an estimate of the limits to which
farm income can be increased in each agro-climatic zone. The last column in Table-31 shows
the possibilities of farm-income enhancements as an average of three top-performing
agricultural households in the respective zones. It shows existence of farming examples in
Gangetic-alluvial and Terai-alluvial zones which earn approximately 4 times more than their
average counterparts (comparison between column 3 and column 5 in Table-31). But for
Lateritic and Coastal saline zones, such frontiers are less than 2 times more. Such differences
arise out of the differences in household characteristics and farmers‟ entrepreneurial skills,
which might not be generated through policy interventions. We can conclude that in each of
these zones, „doubling‟ of farm-income on an average is indeed achievable, but that requires
enough skill development in farming enterprises.
Turning to the effect of credit on farm-income, a similar exercise has been carried out which
is provided in Table-32. The comparability between estimates in Table-32 and that provided
previously (Table-15) is qualified by the similar caution notified in the context of Table-31
before. Table-32, additionally, could provide some estimates on the „marginal effect of
credit‟ on farm income across agro-climatic zones. This was possible as the amounts of credit
deployed by the household in agriculture could be elicited in figures from the respondents
(for irrigation, the sources were elicited while the quantity of irrigation water put to the field
was hard to estimate). In Table-32, estimates of marginal contribution of credit (additional
credit of Rs. 1,00,000) on farm income could be calculated. Also, the required credit for
„doubling of farm income‟ through additional credit deployment was estimated separately for
each agro-climatic zone.
49
Table 32: Effect of credit and its requirement for 'doubling of farm income’
Agro-Climatic
Zones
Average Household Income from Farming activities from 1 Ha land
Households
without any
credit
availed for
agriculture
(Rs.)
Households
with some
credit
availed for
agriculture
(Rs.)
% increase
in annual
income
accounted
by credit
availability
Average
size of
credit
deployed
per
hectare
(Rs.)
Average
credit
requirement
for
„Doubling of
farm income‟
(Rs.)
%
increase
in farm
income
from
additional
credit of
Rs. 1
Lakh
Gangetic Alluvial 41,530 50,605 22 1,63,890 7,49,972 13
Terrai Alluvial 45,998 91,292 98 2,12,851 2,16,166 46
Lateritic 27,714 40,289 45 67,923 1,49,704 67
Coastal Saline 49,199 87,632 78 2,98,807 3,82,513 26
[Source: Primary Survey]
The table shows that provision of additional credit could be more productive in Terai-alluvial
and Coastal saline zones, and less in Lateritic zone. Since the Lateritic zone shows the lowest
farm income in absence of credit, marginal contribution of Rs. 1 lakh credit happens to be
highest in this zone. Going by the same arithmetic, this zone requires the lowest additional
credit to „double‟ its existing average farm income.
Both the tables provided above shows that enhancing farm income through promotion of
micro-irrigation facilities and deployment of more agricultural credit is most productive (in
terms of financial return) in the Lateritic zones of West Bengal.
Rural non-farm sector is largely linked with the diversity in surrounding agriculture. If a rural
area is vibrant in agricultural activities, it opens up the scope for various types of business
related to farm inputs and farm produce. Also, a vibrant agriculture allows the rural people to
buy more industrial goods for consumption purposes. So, it is no wonder that the Terai-
alluvial zones, with the presence of large scale vegetable cultivation and small tea
plantations, shows the highest level of average non-farm business income. This is shown in
Table-33, where the estimates had been arrived at considering that subset of respondent
households which reported to have undertaken Non-Farm business activities in the reporting
year (2017). It is to be noted that Non-Farm business activities are very diverse in nature
(detailed in Appendix-3) and the effect of individual entrepreneurial skills on annual income
(profit) is more pronounced for such activities. Still, averaging of profits from such activities
over all practicing households within a zone might allow us to draw some inference regarding
the effect of credit deployment in such activities. Barring the „business leaders‟ (top three
earning performers for each zones, indicated by last column of Table-33), the average annual
earnings from Non-Farm activities from all zones suggest that most of these activities are
quite petty in nature (column 2 and 3 in Table-33).
50
Table 33: Enhancement of Non-Farm business activities through credit deployment
Agro-
Climatic
Zones
Average Household Income from non-farm activities
Households
without any
credit
availed for
Non-farm
business
(Rs.)
Households
with some
credit
availed for
Non-farm
business
(Rs.)
% increase
in annual
Non-farm
income
accounted
by credit
availability
Average
size of
credit
deployed
per
business
activity
(Rs.)
Average credit
requirement
for „Doubling
of Non-farm
income‟ (Rs.)
% increase
in Non-
farm
income
from
additional
credit of
Rs. 1 Lakh
Potential
Income
frontier
(average of
three leaders
in Non-farm
business)
(Rs.)
Gangetic
Alluvial 35,275 40,974 16 87,120 5,39,211 19 1,28,000
Terai
Alluvial 52,073 81,702 57 67,131 1,17,981 85 2,56,250
Lateritic 32,473 46,300 43 75,000 1,76,144 57 1,75,333
Coastal
Saline 44,120 71,086 61 1,02,000 1,66,885 60 3,66,667
[Source: Primary Survey]
The above table shows that credit used in Non-Farm business earning is comparatively more
useful for Coastal saline zone and Terai-alluvial zone. The coastal saline zone also reported
the highest average level of credit deployment in such activities. It might have been caused
by the prevalence of coastal fishing and fish-related trading activities in that zone. The table
also shows that optimum entrepreneurial interventions leaves the scope for increasing such
incomes more than 3 times (comparison between column 3 and 8) in first three zones while
that is more than 5 times in Coastal saline zone. It is interesting to note that, comparing
Table-32 and Table-33, one might conclude that „Doubling on Non-Farm income‟ can be
achieved with lesser credit deployment compared to that for „Doubling of Farm income‟,
except in the case of Lateritic zone.
Similar exercise has also been carried out for livestock-earning by sample households in
different agro-climatic zones. Estimates in Table-34 had been arrived at by considering
households in each agro-climatic zone who had reported some livestock earning during the
reporting year (2017). The top three performers on this count had been separated out within
each agro-climatic zone, and their average earning is taken as the frontier of such earning
activities corresponding to each zone. The rest are divided into two groups – those who had
deployed some credit in livestock rearing and those who did not.
It is seen that the Lateritic and Terai-alluvial zones are good performers in livestock-based
earning, which is also previously indicated by their relatively higher average livestock
holding (Table-10 before). It shows credit deployed in this sector is more rewarding in
Lateritic and Terai-alluvial zones, while its effect is least in Coastal saline zones. The leaders
in this sector earns more than 4-5 times compared to an average household except for Coastal
saline zone (comparison between column 3 and 8 in Table-34). Moreover, an additional
credit earmarked for deployment on livestock-rearing can make the earning from this sector
more than „double‟ except for the Coastal saline zone. However, such doubling should be
treated with caution as the base is low (column 3 in Table-3). It cannot be said that livestock
51
rearing is a better option than increasing farm income or non-farm business with a given
credit deployment, as the absolute returns from credit might be more if deployed in farming
or non-farm business.
Table 34: Effect of credit on income from livestock-based activities
Agro-Climatic
Zones
Average Household Income from livestock based activities
Households
without
any credit
availed for
Livestock
earning
(Rs.)
Households
with some
credit
availed for
Livestock
earning
(Rs.)
% increase
in annual
Livestock
earning
accounted
by credit
availability
Average
size of
credit
deployed
per
household
(Rs.)
Average
credit
requirement
for
„Doubling
of
Livestock
earning‟
(Rs.)
% increase
in
Livestock
earning
from
additional
credit of
Rs. 1 Lakh
Potential
Income
frontier
(average of
three
leaders in
Livestock
earning)
(Rs.)
Gangetic
Alluvial 4,608 7,713 67 56,798 84,305 119 29,233
Terai Alluvial 7,421 13,984 88 82,536 93,334 107 74,467
Lateritic 7,309 13,973 91 79,500 87,193 115 56,000
Coastal Saline 3,707 5,188 40 86,857 2,17,375 46 11,667
[Source: Primary Survey]
In summary, this section provides some scenario for each agro-climatic zone in West Bengal
regarding the effects of interventions like increase in credit availability and developing
sustainable micro-irrigation projects on farm income, earning from Non-Farm sector and
livestock-based activities. It was found that the effect of micro-irrigation is relatively high in
Lateritic zone. Effect of credit for agriculture can result in the highest percentage change in
return in Terai-alluvial zone. Non-farm business earning can be promoted most effectively in
Coastal saline zone and Livestock rearing activities can be promoted most effectively in the
Lateritic zone.
5.6 The Issue of Farmers’ Clubs
Farmers‟ Clubs (FCs) are often seen as a vehicle for equitable distribution of various
government assistance programmes to the farmers. Such associations also enable the farmers
in a village to organize themselves in a unified body to acquire more bargaining power as
buyers of agricultural inputs and sellers of farm outputs against exploitation by middlemen.
FCs are formal associations which are entitled to get various assistances from agencies like
NABARD under various collective schemes like PKVY. When such a club gets recognition
and assistance from NABARD, they call themselves „NABARD-accredited‟ to point out their
distinguished standing. The study came across four FCs within the sample villages and
collected some basic information on their functioning and activities. Two of them are found
to have obtained some financial assistance from NABARD and the rest two have not.
52
What transpired from the discussions with the office-bearers of these clubs is summarized in
Appendix-4. It was found that the two FCs without NABARD accreditation are clubs that
were promoted by one or more local progressive farmers out of their own realization of
tangible benefits that they could gain by organizing themselves into a unified body. They
roped in some like-minded local farmers to promote the club and they have a specific line of
productive activity where most of the members actively participate and obtain regular
income. These clubs are smaller in their membership strength (15-40 members).
The other two FCs were found to be NABARD accredited. They were effectively formed
with encouragement from the local office of Assistant Director of Agriculture (ADA) and got
their NABARD accreditation through his/her patronage. The main activities of these FCs are
to organize training programmes. It can be sensed that in doing so, they act as organizing
agencies for the local ADA, who finds it easier for executing his local liaison duties and
distribution of various agricultural inputs in a more democratic way through such FCs. The
„inclusiveness‟ of such FCs is also manifested in their larger membership strength (75-100 or
more). Though much bigger in size, these FCs couldn‟t clearly tell us how its members are
getting additional regular income through the membership. The regularity of meetings and
the average percentage of members‟ attendance in those meetings are also lower.
It seems that when there is a specific income augmenting programme that requires co-
operation and consultation of a set of farmers among themselves, a smaller group size is more
effective. A group or club with close to 100 members from the same village are bound to be
heterogeneous in the members‟ individual priorities and aspirations. Group borrowing and
repayment of credit through peer-pressure might fail to work for such a large group. Rather,
proven examples of successful women‟s Self Help Groups (SHGs) in India and in Asia had
shown that the groups need to be more homogeneous in their socio-economic background
and smaller in size.
This study, in its previous sections, had amply demonstrated the lacunae in the institutional
delivery system of state-sponsored farmers‟ assistance programmes. The study feels that
farmers‟ stand to gain much in negotiating with the authorities for credit and insurance when
they are formally united in groups. But the groups have to be constituted by members with
common goals and more or less homogeneous resource endowments. Most importantly, they
need to be smaller in size to be effective in handling joint liabilities as well as collective
assets (like shared agricultural implements provided by the authority). The study
recommends, in its next section, active promotion of smaller sized Farmers‟ Clubs the
operations of which should be in line with women SHGs.
5.7 Justification for possible policy interventions
On delivery of various types of assistance programmes to the farmers in an effective and
more equitable way, the study suggest the delivery system to be outsourced to the Non-
Government Organizations and even to specialized private agencies instead of channelizing
all such schemes to the already over-burdened ADAs. While ADA is the most knowledgeable
official entity and usually the most unbiased institution in assisting farmers, its manpower
resource falls largely short of the required staff strength that is needed to reach out to the
needy farmers adequately. Since staffing the ADA offices is a state matter involving finance
departments, it is understood that the offices cannot be made adequately staffed in the short
run. Involving NGOs and private agencies can be the best and least-cost alternative.
53
The engagement of NGOs or some professional agencies would be purely as a facilitator to
reduce the knowledge gap among the lowly educated farmers and to help them overcome
their reluctance to approach institutions like banks in fear of harassment. The agency/NGO
would be helping the poor and less-educated farmers with paper-works in availing various
central and state sponsored (NABARD financed) Assistance Schemes for rural income
enhancement and diversification (e.g., availing KCC, processing bank documents, helping in
soil testing report done, advising in cropping pattern, promoting model farms, availing
PKVY, PMFBY, PMSY etc). For doing these works professionally, monetary incentive has
to be provided to such agencies and local NGOs should be given a priority. Monetary
incentives should be provided by apex bodies like NABARD which should be proportional to
the number of beneficiaries getting their assistance and/or as a percentage of the money
involved in these facilitated transactions.
On irrigation in rain fed areas, the study recommends scaling up successful projects
conceived under IWMP in rain fed (Lateritic) zone. The exact nature of such projects varies
across different locations depending on local topography and resources. However, there are
examples of success scattered everywhere. The offices of ADA in each Block and Krishi
Vigyan Kendras (KVKs) in each district might be given the responsibility to identify the
successful models and provide the fund estimates for scaling them up within their respective
blocks/districts. In other areas, better irrigation can be facilitated primarily through rainwater
harvesting by excavation and renovation of ponds, maintenance and possible extension of
canals and erecting new check dams. The ADA of each block might be asked to develop
required projects and cost estimates. NABARD can help financing these projects under
various existing programmes.
The problem of better distribution of institutional credit needs some reorganization of the
existing institutional setting. The main bottleneck for farmers in availing loan is the absence
of required title documents for their landholding or other mortgaging assets as well as lack of
education and fear of paper-works. Farmers‟ Clubs in their present form might not be that
effective as they tend to be too big in size and hence inefficient in taking up joint
responsibility. The study recommends promoting small sized Farmers Groups (FG) exactly in
line with women SHGs and with similar motivation of bearing group-responsibility in
repaying agricultural credit. Such groups should be formed by similar set of people with
similar motivation. Ideally FGs should be constituted by 10-15 farmers within the same
landholding class, within same village and practicing similar cropping pattern. These FGs
should be recognized and registered as a body having their own bank accounts. After one-
year of existence and some internal fund mobilization, these groups should be financed and
refinanced exactly like SHGs, but with a larger funding and longer repayment periods that
matches farmers‟ requirements reasonably. Setting up such FGs can be facilitated by outside
agencies like NGOs / other professional agencies.
Apart from new provision and modifications in irrigation and credit front, the study finds that
farmers are most convinced to make changes in their own farming techniques only when
some enterprising fellow villager demonstrates the benefits by realizing more profit through
adaptation of such technologies. In the field surveys, the study frequently found scattered
examples of such enterprising farmers who actually changes the attitudes of his neighbours
and effectively spread awareness of new technologies. In many cases, such model farms did
come up with help and consultancy provided by the KVKs. In West Bengal, KVKs are there
at district level and are creating attractive examples of integrated farming through land
shaping, animal husbandry and pisciculture. Few „progressive‟ farmers are always there to
54
come forward to provide demonstration plots. Such examples created interest in the
neighbourhood, but failed to scale up because of lack of fund provisions. In light of the
population density in West Bengal with the prevalence of marginal and small holders, the
study finds that KVKs can be made more effective if they are present at the block level.
6. Conclusion and policy suggestions
In light of the discussions and observations made before, this study comes up with some
practical suggestions for enhancing rural income in West Bengal. The main takeaway point
revealed in this study is that there are plenty of provisions, sponsored by both central and
state government, for assisting farmers in their pursuit to enhance income. But the real
problem is to channelize the assistance schemes to the farmers‟ doorstep through appropriate
institutional arrangements. It is empirically revealed that the provisions are failing to reach
the intended beneficiaries due to information gaps, which are resulting from inefficient
delivery mechanisms and institutional arrangements.
The recommendations for increasing farmers‟ income in West Bengal, hence, are mostly
concentrating on building and reshaping of delivery institutions dealing with various farmers‟
assistance programmes. One good step towards this has already been taken by the West
Bengal government, in which payment for government procurement of rice is being directly
made to the farmers‟ bank accounts. The practice is supposed to cut into middlemen‟s
income, which was a menace in the traditional procurement process. However, this
mechanism was put into place only a couple of months ago and hence its benefits are yet to
be empirically estimated.
The specific recommendations for enhancing farmers‟ income in West Bengal are provided in
the following section in three sets. First set of recommendations is made for the state as a
whole, involving mainly institutional changes and suggesting collaboration among possible
partners. The second set of recommendations is also provided for the whole state,
highlighting the need for scaling up specific interventions and providing wider coverage to
existing assistance schemes. The third set involves specific recommendations made for
different agro-climatic zones that might be considered as cost-saving and income-enhancing
measures, as is identified as the priority interventions for the specified zones.
6.1 Recommendations for improving institutions for assistance delivery
Small and efficient Farmers‟ Groups (FG) are to be promoted similar to women‟s
Self-Help Groups in each Gram Panchayet area. Such FGs should be provided with
funds in larger quantity and with longer repayment period compared to women SHGs.
Such groups should ideally be formed by 10-15 farmers in the neighbourhood
belonging to the same landholding class. The FGs should be formally recognized and
institutionalized.
For effective delivery of the various ongoing assistance and farmers‟ welfare
schemes, experienced Non-Governmental Organizations and/or specialized
professional agencies are to be engaged purely as facilitators for helping the lowly
educated farmers in availing various schemes‟ benefits. Such engagements should be
on the basis of financial incentives to the facilitating agency.
55
Krishi Vigyan Kendras (KVK) in each district need to be funded to set up their own
extension units in each block of the district and scale up their successful
demonstration projects and create a larger pool of local progressive farmers.
Assistance for income enhancement to rural households in West Bengal should be
specially designed for landless and small landholders. They are the overwhelming
majority in the state. Various current assistance schemes, which are not linked to
landholding size, are being appropriated by the larger landowning households due to
their local clout and proximity with the personnel in the delivering institutions.
6.2 Recommendations for improving various service provisions to farmers
For intensification of cropping and hence increasing return from farming, successful
rainwater harvesting models should be scaled up taking cue from IWMP projects from
rain fed areas. The office of the Assistant Director of Agriculture in each block might
be asked to provide the extent of such project possibilities and corresponding funding
requirement for his block in this regard.
Specialized soil testing laboratories needs to be set up adjacent to ADA offices in
each block either purely by engaging private agencies through financial incentives, or
through PPP model. Soil tests reports should be provided in a time-bound way and it
should be accompanied by expert opinion on the optimum cropping pattern and
fertilizer use for that soil.
Prime Ministers‟ Fasal Bima Yojna (PMFBY) should have much wider coverage in
crops across different seasons in West Bengal compared to its present provisions.
West Bengal is characterised by extensive cultivation of vegetables, most of which
are presently not covered under PMFBY
6.3 Recommendations for increasing farm income in major agro-climatic
zones
The assistance schemes for livestock (free distribution of livestock and fodder) needs
to be more concentrated towards the Lateritic zone as the households in this zone have
a better ongoing practice in livestock maintenance and related activities.
Ongoing IWMP projects in rain fed Lateritic zone should be synchronized with
MGNREGA. The later should be used as a vehicle to create more rainwater
harvesting infrastructure like check-dams and dug-wells in Lateritic zones.
In Terai Alluvial zone, special long term credit schemes should be launched for small
holders who can convert parts of their cropland to small tea plantations. The credit is
needed for them towards land conversion cost and also for the gestation period for
new tea plantations which starts yielding financial returns after three years.
.
In light of much lesser average landholding size in Coastal Saline zone compared to
other zones, potential for enhancing rural household income is more from
56
development of inland fisheries than providing inputs to farming. Special credit
facilities should be provided in this zone for developing brackish water fish farms.
The amount of credit that can be availed through KCC is insufficient for such
enterprise.
In Gangetic Alluvial zone, more warehousing facilities should be made available for
potato and vegetables by enticing private investors with soft loans. Also, for potato
growers, a longer repayment period of credit is recommended as they often distress
sell their output at lower price for repayment of short term loans.
This study provides a set of important baseline estimates for average rural household income
and its composition across four major agro-climatic zones and also across different social
class and landholding size-classes for the state of West Bengal in 2017. The information in
this report can be used as a ready reference to compare changes and to evaluate intervention
programmes in this regard at any future point of time. The study sheds light on major
bottlenecks in different zones as well as for the state as a whole. It provides a definite set of
policy directions, substantiated by appropriate household level primary data, to enhance
farmers‟ income within a short period of time. The study finds that „Doubling farmers‟
income by 2022‟ is indeed possible provided appropriate institutional changes and provisions
are made quickly.
The results in this study, however, have to be interpreted with a word of caution. Due to the
limit imposed by time and resources, this study had to be carried out with approximately 200
households representing each agro-climatic zone. The large extent of socio-economic and
infrastructural variations within each zone had to be captured within a small sample with a
carefully designed multistage sampling scheme. This could only be achieved through a
purposive (but objective) selection of blocks and villages from each zone. Within a sample
village, households were selected by standard stratified random method. But the blocks and
villages were carefully chosen to capture high, medium and low ranks in terms of their
cropping pattern and irrigation infrastructure. Since the relative prevalence or weight of such
blocks and villages vary cross agro-climatic zones, it will be wrong to directly use the
reported estimates as population estimates. While it is perfectly sensible to use the results for
future comparison and identifying bottlenecks, it might not be wise to extrapolate these
results to find estimates for the whole of West Bengal. For that, a larger sample size for each
zone is advisable, which should be supplemented by required secondary information at block
and Gram Panchayet level. It remains another research agenda and open at this point.
References
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Government of India, Available at http://agcensus.nic.in [Last accessed 02.01.2018]
Agricultural Statistics at a Glance (2016), Ministry of Agriculture & Farmers Welfare,
Department of Agriculture, Cooperation & Farmers Welfare, Directorate of Economics and
Statistics. Government of India. Available at http://eands.dacnet.nic.in/PDF/Glance-2016.pdf
[Last accessed 24.03.2018]
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District Statistical Handbook(s) (2014): Department of Planning, Statistics and Programme
Monitoring; Government of West Bengal. Available at
http://www.wbpspm.gov.in/publications/District%20Statistical%20Handbook
[Last accessed 24.03.2018]
Lanjouw P. & A. Shariff (2004): Rural Non-Farm Employment in India: Access, Incomes
and Poverty Impact, Economic and Political Weekly, Vol. 39, No. 40, pp. 4429-4446
Mandal S., D. Burman, U.K. Mandal, T.D. Lama, B. Maji & P.C. Sharma (2017):
Challenges, Options and Strategies for Doubling Farmers‟ Income in West Bengal –
Reflections from Coastal Region, Agricultural Economics Research Review, Vol. 30, pp 89-
100
Meena P.C., R. Kumar, N. Sivaramane, S. Kumar, K. Srinivas, A. Dhandapani & E. Khan
(2017): Non-Farm Income as an Instrument for Doubling Farmers‟ Income: Evidences from
Longitudinal Household Survey, Agricultural Economics Research Review, Vol. 30, pp 127-
137
Nakajima M, K. Otsuka & T. Yamano (2017): Jobs off the Farm: Wealth, Human Capital,
and Social Group in Rural Eastern India, The Journal of Development Studies,
http://dx.doi.org/10.1080/00220388.2017.1283017 [Last accessed 02.01.2018]
NSSO (2014): Key Indicators of Situation of Agricultural Households in India, NSS 70th
Round (January-December 2013), Ministry of Statistics and Programme Implementation,
Govt. of India. Available at
http://mospi.nic.in/sites/default/files/publication_reports/KI_70_33_19dec14.pdf
[Last accessed 02.01.2018]
Singh S. (2018) : Doubling Farmers‟ Incomes Mechanisms and Challenges, Economic &
Political Weekly, Vol. LIII, No. 7, pp 15-19
State Agriculture Plan for West Bengal (prepared by NABCONS & Department of
Agriculture, Government of West Bengal) : Available at
http://rkvy.nic.in/static/SAP/WB/WB.PDF [Last accessed 24.03.2018]
West Bengal Development Report (2010) Planning Commission, Govt. of India;, Academic
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[Last accessed 24.03.2018]
Websites:
Department of Agriculture, Government of West Bengal:
https://wb.gov.in/portal/web/guest/agriculture
58
APPENDIX-1: Location of the Sample districts in West Bengal [Indicated by red marks]
59
APPENDIX-2: Characteristics of sample villages
The specific characteristics of the selected sample villages, as was noted from the FGDs with
ADAs, are as follows:
For District BANKURA
Blo
ck
Village
Main features of the village
Pat
rasa
yar
Hamirpur
1.Three annual crops are cultivated.
2. Irrigation facility is moderate.
3. Road connectivity (with market) is very bad.
4. Women participation rate in income activities is very low.
Birsingha
1. Yearly one crop only.
2. Villagers are mainly depends on other non-farm income activities
3. Poor irrigation facility.
4. Poor transport and communication
Salkhara
1. Yearly two crops
2. very poor road connectivity
3. Moderate irrigation
On
da
Angadpur
1. Remote area (Very poor communication)
2. Mainly one crop produced yearly
3. Poor irrigation system
4. Little modernization in agriculture
5. More than 85 % people are engaged in milk-related production
6. Poor marketing facility
Dubrajpur-Ola
1. Large wholesale market
2. Highly diversified area in terms of crops and vegetables
3. Three times paddy and various vegetables being produced yearly
4. Good irrigation system and road connectivity with good transport
5. Linked with other city markets
Purusottampur
1. yearly three crops are produced
2. collective organized irrigation system
3. crop diversified area
4. Kangshabati Dairy project.
Manjuria
1. River water is only source of irrigation (no submersible)
2. Only one crop (monsoon Paddy) in a year
3. good road connectivity and moderate transport facility
Ch
hat
na
Dalpur
1. Poor irrigation
2. Good road connectivity.
3. Emergence of organic farming
Metyala
1.One annual crop
2.Poor irrigation
3. poor market
4.Moderate road connectivity
Karkari
1. One annual crop
2.Poor irrigation
3 Poor transport facility
4.Tribal population
60
For District BURDWAN
B
lock
Village
Main features of the village
Au
sgra
m-I
Ausgram
1. Poor Irrigation.
2. Road connectivity is good.
3. Different social classes exist.
4. Proximity of rice mill, cold storage.
5. Three crops in a year
Beluti
1. Irrigation Problem. 2.
2. Recently, interventions increased Boro rice cultivation.
3. 50% of the farmers of this village are land less.
4. Pulse production is high due to less irrigational facilities in winter.
5. Road connectivity is good but lack of public transport services.
Gangarampur
(Galigram)
1. Different crops can be produced thrice in a year in 60% of the total land
2. Rate of education is high among the farmers
3. Some farmers have adapted zero tillage for reducing production cost
4. Some low lying land is susceptible to frequent flooding
Bhada
1. Irrigation is very poor
2. Road connectivity is poor.
3. Poor marketing channel
4. Significant Potato Cultivation
Kal
na-
II
Dafarpur
1. Irrigation is very good and efficient crop rotation.
2. A group of farmers started organic farming with the help of PKVY scheme
and a progressive farmers club is initiated with NABARD‟s certification.
3. Road connectivity is not too good and Storage problem.
4. Absence of proper marketing facilities for organic products.
5. Far from “Kishan mandi” and “krishak bazaar”.
6. Most of the farmers are holding soil health card and KCC.
Ramnagar
1. Irrigation & road connectivity are good
2.Lack of good marketing channel.
3. Using drum-seeder technology for sowing crops by govt assistance
4. Within the village a co-operative agricultural development society is
working for farmers‟ welfare, especially providing credit facilities.
Hatgacha
1. Irrigation is good and good crop rotation
2. Farmers are getting benefits of some agricultural schemes (ATMA, RKVY)
3. Strong presence of Jute and Onion cultivators.
4. Under ATMA scheme farmers are availing labour saving zero tillage
5. Presence of village co-operative agricultural development society
6. Proximity to urban centre
7. Lack of storage for onion & Lack of marketing channel
Sal
anp
ur
Barabhuin
1. Soil is infertile, basically lateritic.
2.Irrigation is very poor, Insufficient rainfall
3. Presence of Tribal population
4. Ongoing NABARD assisted programme by a local NGO
Achra
1. Soil is infertile, basically lateritic
2.Insufficient rainfall and poor Irrigation
3. Presence of horticulture project under the MGNREGA scheme.
4. IWMP project for watershed development
5. Road Connectivity is good, but lack of public transport
Jitpur
1. Soil is infertile, basically lateritic.
2. Insufficient rainfall and poor Irrigation
3. Under the NAMSA (National Mission for Sustainable Agriculture) scheme
pisciculture activities is developing.
61
For District JALPAIGURI (Including Newly Formed ALIPURDUAR)
B
lock
Village
Main features of the village
Raj
gan
j
1 No. Takimari
1. Riverbed (Char) area beside Teesta river, no irrigation problem
2. Good vegetable belt
3. Relatively remote
4. Very few households has legal land entitlement
Pipripara-telipara-
jalapara-Purba
debithakurbari
1. Model village (all support schemes are being implemented more intensively
by the local agriculture authority)
2. Not remote
3. Irrigation facility not good
4. Presence of small tea growers
Bholapara-
Chariyapara
1. Near Bangladesh border
2. Relatively remote
3. Irrigation problem exist
4. Heavy concentration of small tea growers
Badlagoch
1. Good transport facility
2. Irrigation facility bad
3. Presence of farmers‟ club
May
nag
uri
Paschim
Barogharia
1. Relatively remote
2. Irrigation facility good (beside teesta river)
3. Vegetable belt
Madhabdanga-
Sarjubala
1. Good transport facility
2. Not near any river, ground water is accessed for irrigation
3. Presence of organic farming
Basilardanga
1. Beside small river, but water is not available throughout the year
2. Recurrent flood problem in monsoon
3. Transport facility is not good
A
lip
urd
uar
-II
Dakhin
Salsalbari-
Golabari
1. Presence of Farmers‟ club, ongoing PKVY project
2. Good road connectivity
3. Close to Alipurduar town, close to market
4. Irrigation facility is medium
Koyakhata
1. Canal side, good irrigation.
2. Transport facility bad
3. Vegetable belt
Jashodanga
1. River encircled, regular flooding
2. Crop variety is high
3. Poor transport facility
4. Existence of Farmers‟ club
62
For District SOUTH 24 PARAGANAS
B
lock
Village
Main features of the village
Pat
har
pra
tim
a
Shridharnagar
1. located on the most remote island in Sundarban delta
2. Dotted with fisheries and a large fishing community
3. saline water ingression in agricultural land is a risk to agriculture
4. Single monsoon crop, no irrigation facility
Achintyanagar
1. On a island in Sundarban delta, with poor connectivity to mainland
2. Betel leaf cultivation is predominant
3. Fish farms are increasing by number
Dakshin Roypur
1. Not on an island (though part of delta area)
2. Road connectivity and transportation is good.
3. There is a strong presence of vegetable cultivators.
4. Irrigation facility is good, presence of shallow tubewells.
Mahendranagar
1. Not on an island (though part of delta area)
2. Road connectivity and transportation is poor.
3. Presence of fishing community and substantial non-farm income
4. Poor Irrigation facility
Mat
hu
rap
ur-
I
Daudpur-
Sekhpukuria
1. Presence of mixed occupation and active SHG groups
2. Irrigation is good.
3. Dairy based activities under the Sundarini project by the State Govt.
4. Road connectivity and transportation is moderate
Narayanipur
1. Mostly agriculture-based, two annual crops
2. Presence of winter vegetables and mustard
3. Remote location and far from the large market.
Baraghoradal
1. Road connectivity is good.
2. Presence of local wholesale market.
3. Irrigation is good.
4. Presence of different Govt. projects (RKVY, PKVY, NFSM, ATMA etc.)
.
Dia
mo
nd
Har
bo
ur
- I
Dakshin Kuleswar
1. Existence of a strong group of vegetable cultivators.
2. Good soil fertility
3. Good road connectivity and proximity to market (Krishak Bazar)
Dakkhin Shaharda
1. Road connectivity is poor
2. Remote and far from nearest town
3 .Vegetable production is good.
Jangalpara
1. Two crops, near Hoogly river
2. Existence of pisciculture.
3. Near to town and the local market
63
APPENDIX-3: Agro-climatic zone wise Frequency distribution of Non-
Farm earning activities of the sample respondents
A3.1 Activity Category: Agriculture-Allied and Natural Resource Based
Brief Description of Activity Agro Climatic Zones
Gangetic Alluvial
Terai Alluvial Lateritic
Coastal Saline
Farm Labour Jobs 133 54 76 44
Tea Garden Labour Jobs 15
Renting out Agricultural Equipments (Tractor/Power Tiller/Pump/Plough etc.) 4 2 2 5
Trading in Rice 1
Trading in Fish 1 3
Trading in Bamboo 1
Trading in Fertilizers 1 1
Trading in Vegetables 3 5 8 8
Making of baskets from bamboo 3
Trading in Betel Nut 9
Trading in Haystacks 1
Trading in Fuel wood 2
Trading in Fruits/Mushroom 1 4 3
Trading in Sal Leaf 2
Making Molasses 1
Nursery business/ Seed trading 1 2 4
Making Parched Rice 1 1 4
Making dish out od Sal leaf 7
Making items from and Trading in Sola (Aeschynomene aspera)
4
Running Poultry Farm 1 5 2 3
Pisciculture 1 5 4
Fishing in open access areas (River/Coast) 5 2 3
Repairing and selling Fishing Nets 1
Livestock Selling 1 1
Trading in milk and making milk products 9 4 13
Non-Farm daily Labour jobs 40 50 70 71
Labour Job in Brick Field 1 2
Labour job in Bidi Making 3
Total 210 153 187 164
64
A3.2 Activity Category: Non-Agriculture related business
Brief Description of Activity Agro Climatic Zones
Gangetic Alluvial
Terai Alluvial Lateritic
Coastal Saline
Iron chest (Almirah) Making Unit 1
Automobile Repairing unit 2 1 1 2
Wooden Furniture Making unit 2 1
Iron grill and gate manufacturing unit 1 1
Ice-cream making unit 1
Husking Mill (Rice/Oilseed) 4 1
Machine Repairing Shop 1
Decorating and Catering business 3 2 1 2
Cloth Merchant 1 1 2
Construction Material Supplier 3 2 2
Sanitary and Hardware Merchant 1 1 1 1
LPG distribution 1
Selling of Lottery tickets 1 1
Grocery / Stationary Shop / Tea stall 21 22 13 25
Mobile (selling/recharging) Shop 1 1 2
Jewellery Shop 1
Medicine Shop 2 1
Meat Shop 3 2
Book Shop 1
Beauty Parlour 1 1
Barber shop 4 2 1
Cyber Café 1
Electrical/Electronic Goods shop 3 1 1 1
Shoe Shop 1
Sweets Shop 1 2 1
Tailoring shop 2 2 4 8
Photography Studio 2 1
Photocopying business 1 2
Other miscellaneous trading and business 1 5 7 4
Total 50 51 40 59
65
A3.3 Activity Category: Migrant labour and Self employed
Brief Description of Activity Agro Climatic Zones
Gangetic Alluvial
Terai Alluvial Lateritic
Coastal Saline
Migrant Labour Jobs (going outside West Bengal) 6 21 7 9
Migrant Labour Jobs (within West Bengal) 5 2 6 6
Driving small transport vehicles (Autorickshaw/Toto/Mechanized Van)
4 17 8 15
Blacksmith 1 6
Carpenter 2 7 2
Illegal Colletion and sale of coal from open pit mines 3
Cook for Mid-Day Meal (through SHGs) 18 2 17 11
Other Self Employed (barber, mechanic, electrician, plumber, etc.)
7 6 11 10
Weaver 6
Potter 2 1
Priest 3 2 1 1
Doctor (Untrained) 2 4 2 1
Private Tutor 4 4 5 3
Artisan and craftsman (wood/clay/metal) 5 8
Agent of Life Insurance Corporation/ Other insurance companies
1 1 2 1
Total 61 67 73 67
A3.4 Activity Category: Government sponsored earning programme and other earnings
Brief Description of Earning
Agro Climatic Zones
Gangetic Alluvial
Terai Alluvial Lateritic
Coastal Saline
Widow Pension 2 1 1 2
Old Age Pension 5 13 5 9
Temporary Salary 21 5 10 19
Temporary Salary (Govt) 1 2 1
Salary Pension 2 1 2
Pension 1 2 4 2
Govt Employee 11 13 4 8
Fishermen Pension 1
Disability Pension 2
Krishi Pension 1 2
Private Emplyoee 6 5 10 5
House Rent 1 1
Car Rent Business 3
Work under MGNREG 56 80 12 30
Total 106 126 51 79
APPENDIX-4: Brief description of Farmers’ Clubs operating in sample villages
Name and address of the Farmer’ Club
Member Strength
Usual Activity Meeting
regularity
Meeting Atten-dance
Benefits to the members and the club
Daudpur Matangini Farmer’s Club, [Established 2011] Mathurapur, South 24 Pgns
39
Members are collectively maintaining a fund for Shola (Aeschynomene aspera) cultivation. The club provides market access to the Shola cultivators to sell their products and also built a shed where various shola-based handicrafts are prepared by the local women. This club also give supports to the big livestock (cow) holders by providing medicine, health care etc. through mobile healthcare van.
Monthly 32-35
Most of the members connected to the club are getting regular income from the handicrafts they make which is collectively marketed in the wholesale market of Kolkata The Club is promoted by a local social worker and the club itself did not get any formal assistance from government departments so far.
Nabin Disha Farmer’s SHG, [Established 2013] Dakshin Salsalabari, Alipurduar
15
One of the main objectives of the group is to promote organic farming among the local farmers. The group also prepares vermicomposting fertilizers and sells it to the local farmers at cheaper rate.
Monthly 15
All members of this group have access to seasonal credit for cultivation from bank through the SHG’s facilitation at monthly 2% rate of interest. Some of them could start businesses like trading in locally available betel nuts and traditional local varieties of rice by using such bank loans. For maintaining the seed bank of local folk rice varieties the club have got Rs. 20,000 rupees twice so far. Beside, the club also has been receiving Rs 1,800 per year under the PKVY scheme since 2015.
Dafarpur Bidhanchandra Farmer’s Ciub, [Established 2014] Kalna-II, Purba Bardhaman
75
The club frequently organises training programmes to promote new farming techniques under the ATMA scheme and on organic farming under the PKVY scheme in collaboration with the local ADA Office. Besides that, recently the club has organised livestock development training programmes for the local women..
Bi-monthly 40
Eighteen farmers of the club have got the facilities for green house cultivation where a considerable amount of subsidy was disbursed by NABARD for setting up green houses. But this project has been facing some local problems for three months. The club got Rs. 7500 once from NABARD to organize a training programme.
Sabujsathi Krishak Sangathan, [Established 2014] Jashodanga, Alipurduar
101
The farmers’ club has been maintaining a seed bank and providing seeds of rice, wheat, mustard, ginger etc. to the farmers. The club frequently organises several agricultural training programmes in collaboration with the local ADA office and Terai Research Centre. In 2017, the club has got a NABARD assisted project for promoting technological interventions in traditional agricultural practices. Recently, the club has started to provide technical supports to the local marginal and small farmers, especially in tillage.
Monthly 75-80
Since 2015, the club has been getting Rs 7500 per year from NABARD for organising annual meetings and agricultural training programmes. In 2017, NABARD sanctioned a project to the club under the ‘Agricultural Machinery Custom Hiring Centre (CHC) Model Scheme’13. Total outlay of this project is Rs 20,00,000 among which NABARD has assisted Rs. 8,00,000 and remaining amount was funded through bank loans and farmer’s private investment.
13 http://agritech.tnau.ac.in/banking/nabard_pdf/Farm%20mechanization/3.Custom_Hiring_Centre.pdf
67
APPENDIX-5: Survey Instrument for households Study on ‘Doubling of Farmers’ Income in West Bengal’ (2017)
[Study Sponsor: NABARD (DEAR), MUMBAI; Principal Investigator; Dr. Santadas Ghosh (Visva-Bharati), Santiniketan] Name of the Gram Panchanyet ___________________________________________ Polling Booth No.___________ Name of the Village_____________________________________________________
Respondent’s Name: ________________________________________
Interviewer’s Name:_______________________________________________________ Date of Interview: _______/______/2017
A. Household Profile:Name of HH head: ____________________________________________________________________ Father / Husband’s Name: __________________________________________
A1. Caste (Put ): 1. SC 2. ST 3. OBC 4. GEN A2. Religion(Put ): 1. Hindu 2. Muslim 3. Christian 4. Other A3. K.C.C(Put ): 1. Yes 2. No
A.4 Member Profile: (HH head name first) (Surname need not be written in table if same)
Mem
ID
Name Age (Yrs)
Sex 1=M 2=F
Edu
catio
n (C
ode)
Relation with head
(Code)
Earning Code (Blank if not earning within six
months) Beneficiary Of (Code)
Documents Possessed (Put √ or Code) Number/s of Bank
Account/s Main Other1 Other2
Ration Card
(Code) AADDHAR PAN
Jan Dhan
Job Card
1 Self
2
3
4
5
6
7
8
9
10
11
12
Education Code: 0=Illiterate; Else highest class passed (1 to 15); 16=Post graduate or above
Relation Code (Relation with head): 1=Wife/Husband2=Son/Daughter 3=Father/Mother 4=Son/Daughter-in-law 5=Brother/Sister 6=Brother/Sister-in-law 7=Grandchildren 8=Other with blood relation9=Other without blood relation
Earning Code: 1=Own Agriculture; 2=Agricultural Labourer;3=Other Non-farm labourer; 4=Salaried Permanent (Govt.); 5=Salaried Permanent (Pvt.);6=Temporary Salary; 7=Own business (Agro-related);8=Own business (Other)
9=Migrant labour within WB; 10=Migrant labour outside WB; 11=Fishery; 12=Fishing; 13=Poultry; 14=Other Livestock / Dairy; 15=NREG; 16=SHG / Group Activities17= Self Employed (Doc/Priest etc).; 18=Other (Specify)
Beneficiary Code: 1=Kanyashree 2=Sabujsathi 3=Others (Spcify) Ration Card Code: 1= APL; 2= BPL;3=AAY;4=SPHH;5=PHH;6=Other
68
B.1: Description of Cultivation in Monsoon, 2016 (Including Leased-in plots)
Plot Sl
No.
Size/Area
Ownership (Code)
Irrigation (Code)
Crop Name
Whether Insured (Code)
Quantity Cost incurred (in Rupees) Avg Selling Price (Per Unit)
Selling Place
(Code) Bigha Katha Produced Sold Unit
(Code) Labour (Hired)
Tillage Seed/sapli
ng
Fertilizer &
Pesticide
irrigation
Approx. Total (If unable to
say separately)
1
2
3
4
5
B.2: Description of Cultivation in Winter, 2016-17 (Including Leased-in plots)
Plot Sl
No.
Size/Area
Ownership (Code)
Irrigation (Code)
Crop Name Whether Insured (Code)
Quantity Cost incurred (in Rupees) Avg Selling Price (Per Unit)
Selling Place
(Code) Bigha Katha Produced Sold Unit
(Code) Labour (Hired)
Tillage Seed/sapli
ng
Fertilizer &
Pesticide
irrigation
Approx. Total (If unable to
say separately)
1
2
3
4
5
69
B.3: Description of Cultivation in Summer, 2017 (Including Leased-in plots)
Plot Sl
No.
Size/Area
Ownership (Code)
Irrigation (Code)
Crop Name Whether Insured (Code)
Quantity Cost incurred (in Rupees) Avg Selling Price (Per Unit)
Selling Place
(Code) Bigha Katha Produced Sold Unit
(Code) Labour (Hired)
Tillage Seed/sapli
ng
Fertilizer &
Pesticide
irrigation
Approx. Total (If unable to
say separately)
1
2
3
4
5
Ownership Code: 1= Owned with title; 2=Owned without title; 3=Leased-in; 4=Leased-out; 5=Any other
Irrigation Code: 1=No irrigation; 2=Shallow; 3=Pond water lifting; 4=Cannel irrigation; 5=Through watershed management; 6=Any other
Insurance Code: 1=Yes; 2=No Unit Code: 1=KG; 2=Mon; 3=Bosta; 4=Quintal [Mention Conversion: 1 Bosta =______KG]
Selling Place Code: 1=himself in local retail market, 2=sold on field (intermediary),3=Nearest wholesale market (auction), 4=MNCs contract, 5=Govt. contract, 6= Kisan Mandi 7= pre-contracted private trader, 8=Sending collectively in city market, 9=Other intermediary 10=any other
B.4 Desired changes & Constraints:
B4.1. Regarding change in intensity
B4.2. Regarding change in technology
B4.3. Regarding crop diversification
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C.1: Details of Income other than Agriculture:
Mem. ID. Activity (Code)
Job description From when (in years)
Approx. Net Income (Annual)
Days/month of engagement in the activity (last year)
Opinion regarding this activity
Days Months
Activity Code: 1= Salaried Pvt. (Permanent); 2= Salaried Govt. (Permanent); 3=Migrant Labour (Outside the State); 4=Migrant Labour (Within the State);
5=Agro related business; 6=Other business; 7=Fishery; 8=Fishing; 9=Poultry; 10=Other livestock/dairy; 11=MGNREGA; 12=Other temporary salary;
13=SHG/other group activities; 14=Self employed professions (Doctor, Priest etc.); 15=Agricultural Labour; 16=Other daily labour; 17=Any Other (Specify).
Opinion code: 1= want to quit this activity, 2= will continue as usual 3= will try to scale up/intensify 4= will try to scale up in a different way/technology/diversification
C.2: Constraints for desired change in these activities:
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D. Awareness about benefit Schemes:
Category Name known (in Short)
Source of knowledge
(code)
Whether applied (Yes=1/ No=2)
Benefit got so far Year of getting benefit
Tenure of benefits
received (code)
Amount mainly utilized
for (code)
Constraint for availing if aware(code)
Agriculture
Education
Health/ Sanitation
Gas/ Electricity
Housing
Livestock
Microfinance (e.g. SHGs)
Others Livelihood
Source of knowledge (code): 1=Panchayat/Municipality, 2=School Teacher, 3=Political Leader, 4=Friends/Relatives, 5=Social Welfare stuff, 6=Anganwari workers, 7=Electronic media (radio/TV/mobile internet),
8=Print media (newspaper), 9=Others
Tenure of benefits received (code): 1=Monthly, 2=Bi-monthly, 3=Quarterly, 4=Half yearly, 5=Yearly, 6=One time, 7=Two times
Amount / goods & services mainly utilized for (code):1=Own consumption, 2=Income enhancement, 3=Saved, 4=Not doing anything, 5=Loan reimbursement, 6=Others
Constraint for availing if aware(code): 1=Political constraint, 2=Own encouragement problem, 3=Document related problem, 4=Information gap/Not aware, 5=Others
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E. Irrigation & Soil testing details:
Plot Id
Soil tested ever (Yes=1/No=2)
year of test Result (Yes=1/No=2)
Follow up benefit
Irrigation Status (code): 1=No irrigation, 2=Shallow/Submersible, 3=Pond water lifting, 4=Cannel/River, 5=Irrigation (e.g. IWMP) from project, 6=Others
Deficit in Irrigation (code): 1=water deficit, 2=High price charge, 3=Electricity problem, 4=Others
F. Storage & Marketing details (for sold products within last one year):
F1. Distance of warehouse: _______________(km) cost of transport________________________(Rs.) per_______________(unit) [Name/s of product kept last year____________________________]
F2. Distance of cold storage: _______________(km) cost of transport________________________(Rs.) per_______________(unit)[Name/s of product kept last year____________________________]
Product Name
Storage details Marketing details
Amount kept in warehouse/ cold store Storing time
Releasing time
Storage cost (per unit for this duration)
Sold to (code)
Selling Price per unit
Comment (if any)
(qty) unit
Sold to (code): 1=himself in local retail market, 2=sold on field (intermediary),3=Nearest wholesale market (auction), 4=MNCs contract, 5=Govt. contract, 6= Kisan Mandi
7= pre-contracted private trader, 8=Sending collectively in city market, 9=Other intermediary 10=any other
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G1. Present Credit Profile and Requirement C
red
it S
l
Mem Name / Mem ID Year Source (Code)
Mortgage (Code)
Main Purpose (Code)
Total Amount
Net Outstanding
Tenure Rate of Interest (%)
Year Month Yearly Monthly
Source Code: 1=S.H.G 2=Farmer’s Society 3= GraminBank4=Other Commercial Banks5=Krishi SamabaySamity5=K.C.C6= BSKP5= Neighbour/Relative6= Mahajan7= Others
Mortgage Code: 0= No Mortgage1= Land2= Gold/Jewellery3= Others
Purpose Code: 1= Agriculture2= Pisciculture3= Animal husbandry4= Health Purpose5= Buy vehicle6= Other business7= Buy land8= Making home or digging pond9= Buy consumable goods 10=Ceremony11=
Others
G2. Requirement for further credit
H: Contract Farming
Contracted Crop
Contract Farming 1= Yes 2=No
Known Person 1= Yes 2=No
Awareness (Code)
Willingness 1= Yes 2=No
Contracting from Year
Awareness Code: 1=Only Heard 2=Know about the Company 3=Tried to start 4=Others
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I: Description of livestock:
Cow Goat Sheep Pig Chicken Duck
1.How many of these animals do you have currently?
2.What is approximate monthly cost (if any) for feed/fodder? (Rs.)
3.Wkat is the approximate total revenue from it last year? (Rs.)
J. Average Expenditure:
Children’s education Health / Medicine Ordinary/Smart phone recharge Smart phone data recharge Aggregate expenditure
Monthly (Average) (Rs.)
K. Any special observation for this household:
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